BibSLEIGH — classification tag

classification

classification

Tag #classification

2687 papers:

EDM-2019-KaserS #interactive #modelling #network #student: Exploring Neural Network Models for the Classification of Students in Highly Interactive Environments (TK, DLS).
EDM-2019-MbouzaoDS #analysis #interactive #student #video: A Methodology for Student Video Interaction Patterns Analysis and Classification (BM, MCD, IS).
ICPC-2019-SchnappingerOPF #learning #maintenance #predict #static analysis #tool support: Learning a classifier for prediction of maintainability based on static analysis tools (MS, MHO, AP, AF), pp. 243–248.
ICSME-2019-KallisSCP #machine learning: Ticket Tagger: Machine Learning Driven Issue Classification (RK, ADS, GC, SP), pp. 406–409.
ICSME-2019-MillsEBKCH #learning #traceability: Tracing with Less Data: Active Learning for Classification-Based Traceability Link Recovery (CM, JEA, AB, GK, SC, SH), pp. 103–113.
MSR-2019-KiehnPC #empirical #using #version control: Empirical study in using version histories for change risk classification (MK, XP, FC), pp. 58–62.
SANER-2019-NghiYJ #algorithm #dependence #network: Bilateral Dependency Neural Networks for Cross-Language Algorithm Classification (BDQN, YY, LJ), pp. 422–433.
CoG-2019-SoaresB #behaviour: Deep Variational Autoencoders for NPC Behaviour Classification (ESS, VB), pp. 1–4.
CIKM-2019-0002CZTZG #graph #named: Meta-GNN: On Few-shot Node Classification in Graph Meta-learning (FZ0, CC, KZ, GT, TZ, JG), pp. 2357–2360.
CIKM-2019-AhmadvandSCA #named #topic: ConCET: Entity-Aware Topic Classification for Open-Domain Conversational Agents (AA, HS, JIC, EA), pp. 1371–1380.
CIKM-2019-CaoZXPY #adaptation #consistency #image #semantics: Adversarial Domain Adaptation with Semantic Consistency for Cross-Domain Image Classification (MC, XZ, YX, YP, BY), pp. 259–268.
CIKM-2019-ChenLX0 #network #sentiment: Sentiment Commonsense Induced Sequential Neural Networks for Sentiment Classification (SC, XL, YX, LH0), pp. 1021–1030.
CIKM-2019-FanBSL #fine-grained #network #prototype #scalability: Large Margin Prototypical Network for Few-shot Relation Classification with Fine-grained Features (MF, YB, MS, PL0), pp. 2353–2356.
CIKM-2019-GozuacikBBC #concept #detection: Unsupervised Concept Drift Detection with a Discriminative Classifier (ÖG, AB, HRB, FC), pp. 2365–2368.
CIKM-2019-GuoAWPC00 #multi #recognition: Multi-stage Deep Classifier Cascades for Open World Recognition (XG, AAF, LW, HP, XC0, KZ0, LZ0), pp. 179–188.
CIKM-2019-HuangCLCHLZZW #approach #multi #network: Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach (WH, EC, QL0, YC, ZH, YL, ZZ, DZ, SW), pp. 1051–1060.
CIKM-2019-HuangWZLC #network #prototype: Deep Prototypical Networks for Imbalanced Time Series Classification under Data Scarcity (CH0, XW, XZ, SL, NVC), pp. 2141–2144.
CIKM-2019-IslamLL00 #random #semantics: A Semantics Aware Random Forest for Text Classification (MZI, JL, JL, LL0, WK0), pp. 1061–1070.
CIKM-2019-KhabiriGVPM #industrial #word: Industry Specific Word Embedding and its Application in Log Classification (EK, WMG, BV, DP, PM), pp. 2713–2721.
CIKM-2019-KimRG #ambiguity #hybrid: Hybrid Deep Pairwise Classification for Author Name Disambiguation (KK, SR, CLG), pp. 2369–2372.
CIKM-2019-LiQWZCZn #visual notation: Domain Knowledge Guided Deep Atrial Fibrillation Classification and Its Visual Interpretation (XL, BQ, JW, XZ, SC, QZ), pp. 129–138.
CIKM-2019-LiuLLZS #identification: Sexual Harassment Story Classification and Key Information Identification (YL, QL, XL, QZ, LS), pp. 2385–2388.
CIKM-2019-RizosHS #learning: Augment to Prevent: Short-Text Data Augmentation in Deep Learning for Hate-Speech Classification (GR, KH, BWS), pp. 991–1000.
CIKM-2019-ShahVLFLTJS #image #multimodal: Inferring Context from Pixels for Multimodal Image Classification (MS, KV, CTL, AF, ZL, AT, CJ, CS), pp. 189–198.
CIKM-2019-ShiRWR #multi #online #sentiment: Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Experts (TS, VR, SW, CKR), pp. 2723–2731.
CIKM-2019-WuH19a: Enriching Pre-trained Language Model with Entity Information for Relation Classification (SW, YH), pp. 2361–2364.
CIKM-2019-WuWLH0 #sentiment: Sentiment Lexicon Enhanced Neural Sentiment Classification (CW, FW, JL, YH, XX0), pp. 1091–1100.
CIKM-2019-YanLWLWZG #image #multi #random #using: Imbalance Rectification in Deep Logistic Regression for Multi-Label Image Classification Using Random Noise Samples (WY, RL, JW, YL, JW, PZ, XG), pp. 1131–1140.
CIKM-2019-YuanLZW: Locally Slope-based Dynamic Time Warping for Time Series Classification (JY, QL, WZ, ZW), pp. 1713–1722.
CIKM-2019-ZhaoCXLZ0 #graph: Hashing Graph Convolution for Node Classification (WZ, ZC, CX, CL, TZ0, JY0), pp. 519–528.
ECIR-p2-2019-PenhaCCGS #automation #documentation #performance #predict: Document Performance Prediction for Automatic Text Classification (GP, RRC, SDC, MAG, RLTS), pp. 132–139.
ICML-2019-BasuGLS #streaming: Pareto Optimal Streaming Unsupervised Classification (SB0, SG, BL, SS), pp. 505–514.
ICML-2019-BeygelzimerPSTW #algorithm #linear #multi #performance: Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case (AB, DP, BS, DT, CYW, CZ), pp. 624–633.
ICML-2019-CotterGJSSWWY #constraints #metric: Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints (AC, MRG, HJ, NS, KS, SW, BEW, SY), pp. 1397–1405.
ICML-2019-GuralM #embedded: Memory-Optimal Direct Convolutions for Maximizing Classification Accuracy in Embedded Applications (AG, BM), pp. 2515–2524.
ICML-2019-HsiehNS: Classification from Positive, Unlabeled and Biased Negative Data (YGH, GN, MS), pp. 2820–2829.
ICML-2019-HuangV: Stable and Fair Classification (LH, NKV), pp. 2879–2890.
ICML-2019-HwangJY #generative #named: HexaGAN: Generative Adversarial Nets for Real World Classification (UH, DJ, SY), pp. 2921–2930.
ICML-2019-LeeYLLLS #generative #robust: Robust Inference via Generative Classifiers for Handling Noisy Labels (KL, SY, KL, HL, BL, JS), pp. 3763–3772.
ICML-2019-LiBS #generative #question #robust: Are Generative Classifiers More Robust to Adversarial Attacks? (YL, JB, YS), pp. 3804–3814.
ICML-2019-LiCW #algorithm #kernel #linear #quantum #sublinear: Sublinear quantum algorithms for training linear and kernel-based classifiers (TL, SC, XW), pp. 3815–3824.
ICML-2019-LiuLWJ #adaptation #approach: Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (HL, ML, JW0, MIJ), pp. 4013–4022.
ICML-2019-MeyerH #kernel #performance #statistics: Optimality Implies Kernel Sum Classifiers are Statistically Efficient (RAM, JH), pp. 4566–4574.
ICML-2019-NamKMPSF #learning #multi #permutation: Learning Context-dependent Label Permutations for Multi-label Classification (JN, YBK, ELM, SP, RS, JF), pp. 4733–4742.
ICML-2019-PolianskiiP #approach #bound #geometry #integration #monte carlo: Voronoi Boundary Classification: A High-Dimensional Geometric Approach via Weighted Monte Carlo Integration (VP, FTP), pp. 5162–5170.
ICML-2019-RechtRSS #question: Do ImageNet Classifiers Generalize to ImageNet? (BR, RR, LS, VS), pp. 5389–5400.
ICML-2019-ReeveK #performance #robust #symmetry: Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise (HWJR, AK), pp. 5401–5409.
ICML-2019-RieckBB #graph #persistent: A Persistent Weisfeiler-Lehman Procedure for Graph Classification (BR, CB, KMB), pp. 5448–5458.
ICML-2019-SatoILT #adaptation #co-evolution: Breaking Inter-Layer Co-Adaptation by Classifier Anonymization (IS, KI, GL, MT), pp. 5619–5627.
ICML-2019-UstunLP: Fairness without Harm: Decoupled Classifiers with Preference Guarantees (BU, YL0, DCP), pp. 6373–6382.
ICML-2019-WhitehillR #automation: Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth (JW, AR), pp. 6757–6765.
ICML-2019-ZhuWS #learning: Learning Classifiers for Target Domain with Limited or No Labels (PZ, HW, VS), pp. 7643–7653.
KDD-2019-HartvigsenSKR #adaptation #network #policy: Adaptive-Halting Policy Network for Early Classification (TH, CS, XK, EAR), pp. 101–110.
KDD-2019-Lin #multi #roadmap: Advances in Cost-sensitive Multiclass and Multilabel Classification (HTL), pp. 3187–3188.
KDD-2019-LiST #higher-order #markov #multi #network #predict #random: Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification (CL, DS, DT), pp. 1141–1151.
KDD-2019-RashedGS #multi: Multi-Relational Classification via Bayesian Ranked Non-Linear Embeddings (AR, JG, LST), pp. 1132–1140.
KDD-2019-TangBMLLK #e-commerce #image #named #scalability: MSURU: Large Scale E-commerce Image Classification with Weakly Supervised Search Data (YT, FB, SM, YL, YL, SK), pp. 2518–2526.
KDD-2019-WuHX #graph #named #network: DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification (JW, JH, JX), pp. 406–415.
KDD-2019-YanZDSSK #named #network: GroupINN: Grouping-based Interpretable Neural Network for Classification of Limited, Noisy Brain Data (YY, JZ, MD, ES, CSS, DK), pp. 772–782.
MoDELS-2019-NguyenRRPI #approach #automation #machine learning #metamodelling #repository: Automated Classification of Metamodel Repositories: A Machine Learning Approach (PTN, JDR, DDR, AP, LI), pp. 272–282.
ICSE-2019-AbadGZF: Supporting analysts by dynamic extraction and classification of requirements-related knowledge (ZSHA, VG, DZ, BHF), pp. 442–453.
ICSE-2019-MolinaDPRAF #data type #invariant: Training binary classifiers as data structure invariants (FM, RD, PP, GR, NA, MFF), pp. 759–770.
ICSE-2019-XiaoWCWG #android #automation #identification #named #user interface: IconIntent: automatic identification of sensitive UI widgets based on icon classification for Android apps (XX, XW, ZC, HW, PG), pp. 257–268.
SLE-2019-WeidmannOR #graph grammar: A feature-based classification of triple graph grammar variants (NW, RO, PR), pp. 1–14.
ASPLOS-2019-TzimpragosMVSS #energy: Boosted Race Trees for Low Energy Classification (GT, AM, DV, DBS, TS), pp. 215–228.
CASE-2019-KarimDHCS #framework: A Framework for Accurate Time Series Classification Based on Partial Observation (FK, HD, SH, SC, AS), pp. 634–639.
CASE-2019-YangLYK #learning #realtime: Investigation of Deep Learning for Real-Time Melt Pool Classification in Additive Manufacturing (ZY, YL, HY, SK), pp. 640–647.
CASE-2019-ZhangLGWL #algorithm #learning #taxonomy: A Shapelet Dictionary Learning Algorithm for Time Series Classification (JZ, XL, LG0, LW, GL), pp. 299–304.
ICPC-2018-HartelAL #api #clustering: Classification of APIs by hierarchical clustering (JH, HA, RL), pp. 233–243.
ICSME-2018-LeClairEM #adaptation #categorisation: Adapting Neural Text Classification for Improved Software Categorization (AL, ZE, CM), pp. 461–472.
ICSME-2018-MillsEH #automation #machine learning #maintenance #traceability: Automatic Traceability Maintenance via Machine Learning Classification (CM, JEA, SH), pp. 369–380.
ICSME-2018-SabettaB #approach #automation #commit: A Practical Approach to the Automatic Classification of Security-Relevant Commits (AS, MB), pp. 579–582.
MSR-2018-MaFCAZM08 #automation #open source: Automatic classification of software artifacts in open-source applications (YM, SF, MC, VA, WZ, MM), pp. 414–425.
SCAM-2018-AlreshedyDGSG #automation: [Engineering Paper] SCC: Automatic Classification of Code Snippets (KA, DD, DMG, VS0, TAG), pp. 203–208.
CIKM-2018-BuyukcakirBC #multi #novel #online: A Novel Online Stacked Ensemble for Multi-Label Stream Classification (AB, HRB, FC), pp. 1063–1072.
CIKM-2018-DeutchF #constraints #named: CEC: Constraints based Explanation for Classifications (DD, NF), pp. 1879–1882.
CIKM-2018-GaurKASDTP #exclamation #health #quote: “Let Me Tell You About Your Mental Health!”: Contextualized Classification of Reddit Posts to DSM-5 for Web-based Intervention (MG, UK, AA, APS, RD, KT, JP), pp. 753–762.
CIKM-2018-LiLCOL #approach #documentation #modelling #topic: Dataless Text Classification: A Topic Modeling Approach with Document Manifold (XL, CL, JC, JO, CL), pp. 973–982.
CIKM-2018-MengSZ0: Weakly-Supervised Neural Text Classification (YM, JS, CZ0, JH0), pp. 983–992.
CIKM-2018-TiwariM #framework #towards: Towards a Quantum-Inspired Framework for Binary Classification (PT, MM), pp. 1815–1818.
CIKM-2018-WangM #multi #sentiment: Multi-Emotion Category Improving Embedding for Sentiment Classification (SW, XM0), pp. 1719–1722.
CIKM-2018-WangXWCC #named: DualBoost: Handling Missing Values with Feature Weights and Weak Classifiers that Abstain (WW, JX0, YW0, CC, FC0), pp. 1543–1546.
CIKM-2018-WuWL #learning #multi #sentiment: Imbalanced Sentiment Classification with Multi-Task Learning (FW, CW, JL), pp. 1631–1634.
CIKM-2018-WuZA #graph #learning: A Quest for Structure: Jointly Learning the Graph Structure and Semi-Supervised Classification (XW, LZ, LA), pp. 87–96.
CIKM-2018-ZhuangJYL #coordination #manycore #parallel: Naive Parallelization of Coordinate Descent Methods and an Application on Multi-core L1-regularized Classification (YZ, YCJ, GXY, CJL), pp. 1103–1112.
ECIR-2018-Jalan0V #learning #using: Medical Forum Question Classification Using Deep Learning (RSJ, MG0, VV), pp. 45–58.
ECIR-2018-SuFMMO #multi #on the #twitter: On Refining Twitter Lists as Ground Truth Data for Multi-community User Classification (TS, AF, RM, CM, IO), pp. 765–772.
ICML-2018-AgarwalBD0W #approach #reduction: A Reductions Approach to Fair Classification (AA, AB, MD, JL0, HMW), pp. 60–69.
ICML-2018-BaoNS #similarity: Classification from Pairwise Similarity and Unlabeled Data (HB, GN, MS), pp. 461–470.
ICML-2018-HanHZ #estimation #multi #problem #scalability: Candidates vs. Noises Estimation for Large Multi-Class Classification Problem (LH, YH, TZ), pp. 1885–1894.
ICML-2018-HuNSS #learning #question #robust: Does Distributionally Robust Supervised Learning Give Robust Classifiers? (WH, GN, IS, MS), pp. 2034–2042.
ICML-2018-KennamerKIS #learning #named: ContextNet: Deep learning for Star Galaxy Classification (NK, DK, ATI, FJSL), pp. 2587–2595.
ICML-2018-LiangSLS #comprehension #network: Understanding the Loss Surface of Neural Networks for Binary Classification (SL, RS, YL, RS), pp. 2840–2849.
ICML-2018-RuffGDSVBMK: Deep One-Class Classification (LR, NG, LD, SAS, RAV, AB, EM, MK), pp. 4390–4399.
ICML-2018-SanturkarSM: A Classification-Based Study of Covariate Shift in GAN Distributions (SS, LS, AM), pp. 4487–4496.
ICML-2018-WehrmannCB #multi #network: Hierarchical Multi-Label Classification Networks (JW, RC, RCB), pp. 5225–5234.
ICML-2018-YanKZR #metric: Binary Classification with Karmic, Threshold-Quasi-Concave Metrics (BY, OK, KZ, PR), pp. 5527–5536.
ICPR-2018-AfonsoPSP #learning #using: Improving Optimum- Path Forest Classification Using Unsupervised Manifold Learning (LCSA, DCGP, ANdS, JPP), pp. 560–565.
ICPR-2018-ChenDHLH #automation #clustering #image #performance: Improving Image Classification Performance with Automatically Hierarchical Label Clustering (ZC, CD, LH, DL, HH), pp. 1863–1868.
ICPR-2018-ChenWWK #approximate #image #kernel #set: Riemannian kernel based Nyström method for approximate infinite-dimensional covariance descriptors with application to image set classification (KXC, XJW, RW, JK), pp. 651–656.
ICPR-2018-ChenYY #image #network: Semi-supervised convolutional neural networks with label propagation for image classification (LC, SY, MY0), pp. 1319–1324.
ICPR-2018-ChooSJC #multi #network: Multi-scale Recurrent Encoder-Decoder Network for Dense Temporal Classification (SKC, WS, DjJ, NIC), pp. 103–108.
ICPR-2018-CuiLZLXGJZ #network: Classification Guided Deep Convolutional Network for Compressed Sensing (WC, SL, SZ, YL0, HX, XG, FJ0, DZ), pp. 2905–2910.
ICPR-2018-DasRBP #documentation #image #learning #network: Document Image Classification with Intra-Domain Transfer Learning and Stacked Generalization of Deep Convolutional Neural Networks (AD, SR, UB, SKP), pp. 3180–3185.
ICPR-2018-DuanMKY #image #using: A New Single Image Super-resolution Method Using SIMK-based Classification and ISRM Technique (PD, AM, XK, CY), pp. 3043–3048.
ICPR-2018-ElmogyZEE #3d #automation #framework #network: An Automated Classification Framework for Pressure Ulcer Tissues Based on 3D Convolutional Neural Network (ME, BGZ, ASE, AEB), pp. 2356–2361.
ICPR-2018-FonalZW #algorithm #composition: Feature-Fusion HALS-based Algorithm for Linked CP Decomposition Model in Application to Joint EMG/MMG Signal Classification (KF, RZ, AW), pp. 928–933.
ICPR-2018-GaoSXL #image #kernel #linear #set: Kernel Dual Linear Regression for Face Image Set Classification (XG, QS, HX, YL), pp. 1542–1547.
ICPR-2018-GarciaLSH #complexity #metric #recommendation #using: Classifier Recommendation Using Data Complexity Measures (LPFG, ACL, MCPdS, TKH), pp. 874–879.
ICPR-2018-GuoHSY #multi #rank: Low Rank Multi-Label Classification with Missing Labels (BG, CH, JS, DY), pp. 417–422.
ICPR-2018-HanZG #composition #multi #network: Multi-Frequency Decomposition with Fully Convolutional Neural Network for Time Series Classification (YH, SZ, ZG), pp. 284–289.
ICPR-2018-HouMZ #algorithm: A Voting-Near-Extreme-Learning-Machine Classification Algorithm (HRH, QHM, XNZ), pp. 237–241.
ICPR-2018-JiangL #collaboration #representation: Discriminative Collaborative Representation and Its Application to Audio Signal Classification (YJ, FHFL), pp. 31–36.
ICPR-2018-JiaXD #image: Extended Morphological Profile-based Gabor Wavelets for Hyperspectral Image Classification (SJ, HX, XD), pp. 782–787.
ICPR-2018-JiaZXZH #feature model: Superpixel-Based Feature Extraction and Fusion Method for Hyperspectral and LiDAR Classification (SJ, MZ, JX, JZ, QH), pp. 764–769.
ICPR-2018-KangLS #image: Object Classification of Remote Sensing Images Based on Partial Randomness Supervised Discrete Hashing (TK, YL, QSS), pp. 1935–1940.
ICPR-2018-KurzendorferBSB #analysis #random #segmentation #using: Myocardial Scar Segmentation in LGE-MRI using Fractal Analysis and Random Forest Classification (TK, KB, SS, AB, CF, AKM), pp. 3168–3173.
ICPR-2018-LeiZH0HL #learning #multi #rank: Multi-classification of Parkinson's Disease via Sparse Low-Rank Learning (HL, YZ, ZH, FZ0, LH, BL), pp. 3268–3272.
ICPR-2018-LiangYLH #using: A Segmented Local Offset Method for Imbalanced Data Classification Using Quasi-Linear Support Vector Machine (PL, XY, WL, JH), pp. 746–751.
ICPR-2018-LiCY #feature model #generative #image: Generative Band Feature Enhancement for Hyperspectral Image Classification (JL, FC, DY), pp. 1918–1923.
ICPR-2018-LingLZG #image #learning #network: Semi-Supervised Learning via Convolutional Neural Network for Hyperspectral Image Classification (ZL, XL, WZ, SG), pp. 1–6.
ICPR-2018-LiuDJQ #image #network #visual notation: Visual Tree Convolutional Neural Network in Image Classification (YL, YD, RJ, PQ), pp. 758–763.
ICPR-2018-LiuDWZWZ #education #image #learning: Teaching Squeeze-and-Excitation PyramidNet for Imbalanced Image Classification with GAN-based Curriculum Learning (JL, AD, CW0, HZ, NW0, BZ), pp. 2444–2449.
ICPR-2018-LiuF #sentiment: Introduce More Characteristics of Samples into Cross-domain Sentiment Classification (WL, XF), pp. 25–30.
ICPR-2018-LiuHH #network: Lifting Scheme Based Deep Network Model for Remote Sensing Imagery Classification (XL, BH, CH), pp. 688–693.
ICPR-2018-LiuLKDYZYJY #collaboration #framework #optimisation #representation: A joint optimization framework of low-dimensional projection and collaborative representation for discriminative classification (XL0, ZL, LK, ZD, JY, YZ, CY0, PJ, JY), pp. 1493–1498.
ICPR-2018-LiuZKDYWLJY #image: Data Augmentation via Latent Space Interpolation for Image Classification (XL0, YZ, LK, ZD, JY, JW, SL, PJ, JY), pp. 728–733.
ICPR-2018-LuYY #image: Getting Rid of Night: Thermal Image Classification Based on Feature Fusion (GL, HY, CY), pp. 2827–2832.
ICPR-2018-LyuYCZZ #detection #learning: Learning Fixation Point Strategy for Object Detection and Classification (JL0, ZY, DC, YZ, HZ), pp. 2081–2086.
ICPR-2018-MaO0TL: EMD-Based Entropy Features for micro-Doppler Mini-UAV Classification (XM, BSO, LS0, KAT, ZL), pp. 1295–1300.
ICPR-2018-MuhammadWCA #architecture #image: Pre-trained VGGNet Architecture for Remote-Sensing Image Scene Classification (UM, WW, SPC, SA), pp. 1622–1627.
ICPR-2018-MutasimBTIA #video: Effect of Artefact Removal Techniques on EEG Signals for Video Category Classification (AKM, MRB, RST, MKI, MAA), pp. 3513–3518.
ICPR-2018-NieLQZJ #algorithm #incremental #learning #multi: An Incremental Multi-view Active Learning Algorithm for PolSAR Data Classification (XN, YL, HQ, BZ0, ZPJ), pp. 2251–2255.
ICPR-2018-PramerdorferKL #3d #bound #multi #network: Multi-View Classification and 3D Bounding Box Regression Networks (CP, MK, MVL), pp. 734–739.
ICPR-2018-RedaGSEEAEEKE #novel #precise: A Novel ADCs-Based CNN Classification System for Precise Diagnosis of Prostate Cancer (IR, MG, AS0, ME, AAEF, BOA, MAEG, AE, RK, AEB), pp. 3923–3928.
ICPR-2018-RosenfeldU #concept: Action Classification via Concepts and Attributes (AR, SU), pp. 1499–1505.
ICPR-2018-RoyBM #visual notation: Discriminative Latent Visual Space For Zero-Shot Object Classification (AR, BB, VM), pp. 2552–2557.
ICPR-2018-SongLXG #encoding #multi #robust: Multi-Scale Cross-Band Encoding of Sectored Local Binary Pattern for Robust Texture Classification (TS, LL, LX, CG), pp. 1163–1168.
ICPR-2018-SongXLG #invariant: Completed Grayscale-Inversion and Rotation Invariant Local Binary Pattern for Texture Classification (TS, LX, LL, CG), pp. 2642–2647.
ICPR-2018-SuHK #analysis #component #multi #performance #using: Efficient Text Classification Using Tree-structured Multi-linear Principal Component Analysis (YS, YH, CCJK), pp. 585–590.
ICPR-2018-SunLHW #algorithm #array #multi: A New ECOC Algorithm for Multiclass Microarray Data Classification (MS, KL, QH, BW), pp. 454–458.
ICPR-2018-TayanovKS #learning #predict #using: Prediction-based classification using learning on Riemannian manifolds (VT, AK, CYS), pp. 591–596.
ICPR-2018-TheagarajanGB #automation #generative #named: DeephESC: An Automated System for Generating and Classification of Human Embryonic Stem Cells (RT, BXG, BB), pp. 3826–3831.
ICPR-2018-TuggenerESPS #dataset #detection #segmentation: DeepScores-A Dataset for Segmentation, Detection and Classification of Tiny Objects (LT, IE, JS, MP, TS), pp. 3704–3709.
ICPR-2018-WangWCK #image #learning #metric #multi #set: Multiple Manifolds Metric Learning with Application to Image Set Classification (RW, XJW, KXC, JK), pp. 627–632.
ICPR-2018-WangYGC #feature model: Feature Selection Ensemble for Symbolic Data Classification with AHP (MW, XY, CG, YC), pp. 868–873.
ICPR-2018-WangYHYP #image: Enhancing Pix2Pix for Remote Sensing Image Classification (XW, HY, CH, JY, CP), pp. 2332–2336.
ICPR-2018-WangZTL #representation #robust: Cauchy Matching Pursuit for Robust Sparse Representation and Classification (YW, CZ, YYT, LL), pp. 694–698.
ICPR-2018-WeiCYLL #black box #image #using: Explain Black-box Image Classifications Using Superpixel-based Interpretation (YW, MCC, YY, SNL, SL), pp. 1640–1645.
ICPR-2018-Windeatt #analysis #optimisation #using: Optimising Ensemble of Two-Class classifiers using Spectral Analysis (TW), pp. 710–715.
ICPR-2018-WitmerB #image #learning #multi #using: Multi-label Classification of Stem Cell Microscopy Images Using Deep Learning (AW, BB), pp. 1408–1413.
ICPR-2018-WuSZZSLPB #fourier #image: Fourier Transform based Features for Clean and Polluted Water Image Classification (XW, PS, LZ, HZ, JS, TL, UP0, MB), pp. 1707–1712.
ICPR-2018-XieHLHYL #network: Deeply Supervised Residual Network for HEp-2 Cell Classification (HX, YH, HL, TH, ZY, BL), pp. 699–703.
ICPR-2018-Yan0R #framework #performance #representation #scalability: An Efficient Deep Representation Based Framework for Large-Scale Terrain Classification (YY, AR0, SR), pp. 940–945.
ICPR-2018-YangZWQ #analysis #detection #image #quality #recognition: Quality Classified Image Analysis with Application to Face Detection and Recognition (FY, QZ0, MW, GQ), pp. 2863–2868.
ICPR-2018-Ye0 #image #invariant #learning: Rotational Invariant Discriminant Subspace Learning For Image Classification (QY, ZZ0), pp. 1217–1222.
ICPR-2018-YeDW #graph: Graph-based Semi-supervised Classification with CRF and RNN (ZY, YD, FW), pp. 403–408.
ICPR-2018-ZhangLYGGZ #fine-grained: Fine-Grained Age Group Classification in the wild (KZ0, NL, XY, XG, CG, ZZ), pp. 788–793.
ICPR-2018-ZhangLZXSL #network: Spatial Pyramid Dilated Network for Pulmonary Nodule Malignancy Classification (GZ, YL, DZ, YX, YS, JL), pp. 3911–3916.
ICPR-2018-ZhangMWZ0 #scalability #semantics #video: From Text to Video: Exploiting Mid-Level Semantics for Large-Scale Video Classification (JZ0, KM, XW0, YZ0, JF0), pp. 1695–1700.
ICPR-2018-ZhangZDW #image #network: Image Exploration Procedure Classification with Spike-timing Neural Network for the Blind (TZ, TZ, BSD, JPW), pp. 3256–3261.
ICPR-2018-ZhangZW #lightweight #named #network: LD-CNN: A Lightweight Dilated Convolutional Neural Network for Environmental Sound Classification (XZ, YZ, WW), pp. 373–378.
ICPR-2018-ZhaoMS #image #named #network: Retraining: A Simple Way to Improve the Ensemble Accuracy of Deep Neural Networks for Image Classification (KZ, TM, ES), pp. 860–867.
ICPR-2018-ZhengZ #approach #network: Accelerating the Classification of Very Deep Convolutional Network by A Cascading Approach (WZ, ZZ), pp. 355–360.
ICPR-2018-Zhuang0CW #learning #multi: Multi-task Learning of Cascaded CNN for Facial Attribute Classification (NZ, YY0, SC, HW), pp. 2069–2074.
ICPR-2018-ZhuDR #feature model #flexibility #image: Flexible and Discriminative Non-linear Embedding with Feature Selection for Image Classification (RZ, FD, YR), pp. 3192–3197.
KDD-2018-LeeRK #graph #using: Graph Classification using Structural Attention (JBL, RAR, XK), pp. 1666–1674.
KDD-2018-LiY #learning #network #policy: Learning Adversarial Networks for Semi-Supervised Text Classification via Policy Gradient (YL, JY), pp. 1715–1723.
KDD-2018-Sirosh: Planet-Scale Land Cover Classification with FPGAs (JS), p. 2877.
KDD-2018-YangWZL0 #multi #network: Complex Object Classification: A Multi-Modal Multi-Instance Multi-Label Deep Network with Optimal Transport (YY, YFW, DCZ, ZBL, YJ0), pp. 2594–2603.
KDD-2018-ZhaoAS0 #dependence #performance #predict #using: Prediction-time Efficient Classification Using Feature Computational Dependencies (LZ0, AAF, MS, KZ0), pp. 2787–2796.
ICMT-2018-BruelCGJKLMSV #comparison #metamodelling #model transformation #reuse: Model Transformation Reuse Across Metamodels — A Classification and Comparison of Approaches (JMB, BC, EG, JMJ, JK, JdL, GM, ES, HV), pp. 92–109.
ICSE-2018-RuscioFMM #collaboration #framework #modelling #re-engineering #research: Collaborative model-driven software engineering: a classification framework and a research map (DDR, MF, HM, IM), p. 535.
CASE-2018-NeumannNKM #learning: Material Classification through Knocking and Grasping by Learning of Structure-Borne Sound under Changing Acoustic Conditions (MN, KN, IK, ZCM), pp. 1269–1275.
CASE-2018-SussDA #approach #automation #component: An approach to automatically assign mechatronic components to an existing or identified classification (SS, CD, FA), pp. 1525–1529.
ICST-2018-FengJ0F #empirical #multi #problem: An Empirical Study on Software Failure Classification with Multi-label and Problem-Transformation Techniques (YF0, JAJ, ZC0, CF), pp. 320–330.
EDM-2017-GautamSSRG #modelling: Modeling Classifiers for Virtual Internships Without Participant Data (DG, ZS, DWS, VR, ACG).
EDM-2017-KlinglerWKSG #performance #student: Efficient Feature Embeddings for Student Classification with Variational Auto-encoders (SK, RW, TK, BS, MHG).
EDM-2017-RomeroEGGM #automation #learning #towards: Towards Automatic Classification of Learning Objects: Reducing the Number of Used Features (CR, PGE, EG, AZG, VHM).
ICSME-2017-TerdchanakulHPM #debugging #n-gram #using: Bug or Not? Bug Report Classification Using N-Gram IDF (PT, HH, PP, KM), pp. 534–538.
MSR-2017-GhotraMH #fault #feature model #modelling #scalability: A large-scale study of the impact of feature selection techniques on defect classification models (BG, SM, AEH), pp. 146–157.
MSR-2017-NiL #effectiveness #predict #using: Cost-effective build outcome prediction using cascaded classifiers (AN, ML0), pp. 455–458.
MSR-2017-Patil #concept #fault: Concept-based classification of software defect reports (SP), pp. 182–186.
MSR-2017-RajbahadurWKH #fault #modelling #using: The impact of using regression models to build defect classifiers (GKR, SW0, YK, AEH), pp. 135–145.
CIG-2017-GoudelisTKK #3d #effectiveness #feature model: 3D cylindrical trace transform based feature extraction for effective human action classification (GG, GT, KK, SDK), pp. 96–103.
CIKM-2017-ChengZZKZW #network #sentiment: Aspect-level Sentiment Classification with HEAT (HiErarchical ATtention) Network (JC, SZ, JZ, IK, XZ0, HW0), pp. 97–106.
CIKM-2017-DangCWZC #kernel #learning: Unsupervised Matrix-valued Kernel Learning For One Class Classification (SD, XC, YW0, JZ, FC0), pp. 2031–2034.
CIKM-2017-HaqueWCDKH #multi #named #online: FUSION: An Online Method for Multistream Classification (AH, ZW, SC, BD, LK, KWH), pp. 919–928.
CIKM-2017-HuangYLP #adaptation: Length Adaptive Recurrent Model for Text Classification (ZH, ZY, SL, RP), pp. 1019–1027.
CIKM-2017-HuPJL #graph #network: Graph Ladder Networks for Network Classification (RH, SP, JJ0, GL), pp. 2103–2106.
CIKM-2017-PatwariGB #detection #multi #named: TATHYA: A Multi-Classifier System for Detecting Check-Worthy Statements in Political Debates (AP, DG, SB), pp. 2259–2262.
CIKM-2017-SchaferL #performance: Fast and Accurate Time Series Classification with WEASEL (PS0, UL), pp. 637–646.
CIKM-2017-SuzannaA: Hierarchical Module Classification in Mixed-initiative Conversational Agent System (SXYS, ALL), pp. 2535–2538.
CIKM-2017-VeysehEDL: A Temporal Attentional Model for Rumor Stance Classification (APBV, JE, DD, DL), pp. 2335–2338.
CIKM-2017-XuWXQ #graph #network #recursion: Attentive Graph-based Recursive Neural Network for Collective Vertex Classification (QX, QW, CX, LQ), pp. 2403–2406.
CIKM-2017-YeHHCLQS #using: Nationality Classification Using Name Embeddings (JY, SH, YH, BC, ML, HQ, SS), pp. 1897–1906.
CIKM-2017-ZhuRXLYW #clustering #pattern matching #social: Cluster-level Emotion Pattern Matching for Cross-Domain Social Emotion Classification (EZ, YR, HX0, YL, JY0, FLW), pp. 2435–2438.
ECIR-2017-BaruaP #query #using: Named Entity Classification Using Search Engine's Query Suggestions (JB, DP), pp. 612–618.
ECIR-2017-McDonaldMO #semantics #using #word: Enhancing Sensitivity Classification with Semantic Features Using Word Embeddings (GM, CM, IO), pp. 450–463.
ECIR-2017-ValavanisSK #image #modelling: Fusion of Bag-of-Words Models for Image Classification in the Medical Domain (LV, SS, TK), pp. 134–145.
ICML-2017-BeckhamP #probability: Unimodal Probability Distributions for Deep Ordinal Classification (CB, CJP), pp. 411–419.
ICML-2017-DembczynskiKKN #analysis #consistency #revisited: Consistency Analysis for Binary Classification Revisited (KD, WK, OK, NN), pp. 961–969.
ICML-2017-FutomaHH #detection #learning #multi #process: Learning to Detect Sepsis with a Multitask Gaussian Process RNN Classifier (JF, SH, KAH), pp. 1174–1182.
ICML-2017-JerniteCS #estimation #learning: Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation (YJ, AC, DAS), pp. 1665–1674.
ICML-2017-KrishnamurthyAH #learning: Active Learning for Cost-Sensitive Classification (AK, AA, TKH, HDI, JL0), pp. 1915–1924.
ICML-2017-OdenaOS #image #synthesis: Conditional Image Synthesis with Auxiliary Classifier GANs (AO, CO, JS), pp. 2642–2651.
ICML-2017-RealMSSSTLK #evolution #image #scalability: Large-Scale Evolution of Image Classifiers (ER, SM, AS, SS, YLS, JT, QVL, AK), pp. 2902–2911.
ICML-2017-SakaiPNS: Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data (TS, MCdP, GN, MS), pp. 2998–3006.
ICML-2017-ThiLNT #probability #problem: Stochastic DCA for the Large-sum of Non-convex Functions Problem and its Application to Group Variable Selection in Classification (HALT, HML, PDN, BT), pp. 3394–3403.
ICML-2017-UbaruM #multi #testing: Multilabel Classification with Group Testing and Codes (SU, AM), pp. 3492–3501.
ICML-2017-Villacampa-Calvo #multi #process #scalability #using: Scalable Multi-Class Gaussian Process Classification using Expectation Propagation (CVC, DHL), pp. 3550–3559.
ICML-2017-YangKT #network #video: Tensor-Train Recurrent Neural Networks for Video Classification (YY, DK, VT), pp. 3891–3900.
KDD-2017-AndersonM #machine learning: Machine Learning for Encrypted Malware Traffic Classification: Accounting for Noisy Labels and Non-Stationarity (BA, DAM), pp. 1723–1732.
KDD-2017-Tagami #approximate #multi #named #nearest neighbour: AnnexML: Approximate Nearest Neighbor Search for Extreme Multi-label Classification (YT), pp. 455–464.
KDD-2017-YenHDRDX #named #parallel: PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification (IEHY, XH, WD0, PR, ISD, EPX), pp. 545–553.
Onward-2017-WrennK #design #error message #fault #process: Error messages are classifiers: a process to design and evaluate error messages (JW, SK), pp. 134–147.
ASE-2017-Mills #automation #towards #traceability: Towards the automatic classification of traceability links (CM), pp. 1018–1021.
ESEC-FSE-2017-Mills #automation #traceability: Automating traceability link recovery through classification (CM), pp. 1068–1070.
GPCE-2017-LinsbauerBG: A classification of variation control systems (LL, TB, PG), pp. 49–62.
CASE-2017-ChenWWWC #big data #detection #fault #multi: Big data analytic for multivariate fault detection and classification in semiconductor manufacturing (YJC, BCW, JZW, YCW, CFC), pp. 731–736.
CASE-2017-LiXLK #approach #learning #physics: Improving colorectal polyp classification based on physical examination data - A ensemble learning approach (CL, XX, JL, NK), pp. 193–194.
CASE-2017-TanCT #automation #evaluation #layout #multi: Multiple binary classifiers to analyse decision of non-compliance: For automated evaluation of piping layout (WCT, IMC, HKT), pp. 80–85.
CAV-2017-AdimoolamDDKJ #embedded: Classification and Coverage-Based Falsification for Embedded Control Systems (ASA, TD, AD, JK, XJ), pp. 483–503.
JCDL-2016-BornandBS #using: Routing Memento Requests Using Binary Classifiers (NJB, LB, HVdS), pp. 63–72.
EDM-2016-AtapattuFT #approach #topic #visual notation: Topic-wise Classification of MOOC Discussions: A Visual Analytics Approach (TA, KF, HT), pp. 276–281.
EDM-2016-BhatnagarDLC #physics #self #student: Text Classification of Student Self-Explanations in College Physics Questions (SB, MCD, NL, ESC), pp. 571–572.
EDM-2016-RusBMMRY #online #tutorial: Preliminary Results On Dialogue Act and Subact Classification in Chat-based Online Tutorial Dialogues (VR, RB, NM, DMM, SR, MY), pp. 630–631.
SANER-2016-DamZ #identification #natural language: Software Language Identification with Natural Language Classifiers (JKvD, VZ), pp. 624–628.
SANER-2016-FontanaDWYZ #concept #smell: Antipattern and Code Smell False Positives: Preliminary Conceptualization and Classification (FAF, JD0, BW, AY, MZ), pp. 609–613.
IFM-2016-ChenAGSM #behaviour #on the #robust #verification: On Robust Malware Classifiers by Verifying Unwanted Behaviours (WC, DA0, ADG, CAS, IM), pp. 326–341.
CIG-2016-ClericoCPMTFGJ #game studies #predict #video: Biometrics and classifier fusion to predict the fun-factor in video gaming (AC, CC, MP, PEM, ST, THF, JCG, PLJ), pp. 1–8.
CIG-2016-DeboeverieRAVP #game studies #gesture #machine learning: Human gesture classification by brute-force machine learning for exergaming in physiotherapy (FD, SR, GA, PV, WP), pp. 1–7.
DiGRA-FDG-2016-KnauerM #game studies #visual notation: Two Worlds, One Gameplay: A Classification of Visual AR Games (MK, JM).
CIKM-2016-BonabC #data type #framework #online: A Theoretical Framework on the Ideal Number of Classifiers for Online Ensembles in Data Streams (HRB, FC), pp. 2053–2056.
CIKM-2016-ChandraHKA #adaptation #framework #multi: An Adaptive Framework for Multistream Classification (SC, AH, LK, CCA), pp. 1181–1190.
CIKM-2016-CormackG #learning #reliability #scalability: Scalability of Continuous Active Learning for Reliable High-Recall Text Classification (GVC, MRG), pp. 1039–1048.
CIKM-2016-GongC #modelling #sequence: Model-Based Oversampling for Imbalanced Sequence Classification (ZG, HC), pp. 1009–1018.
CIKM-2016-LiKZH #network #on the: On Transductive Classification in Heterogeneous Information Networks (XL, BK, YZ, ZH0), pp. 811–820.
CIKM-2016-LiLF #approach #multi: Multi-View Time Series Classification: A Discriminative Bilinear Projection Approach (SL0, YL, YF0), pp. 989–998.
CIKM-2016-LiSLNF #knowledge base #named #topic #twitter #word: TweetSift: Tweet Topic Classification Based on Entity Knowledge Base and Topic Enhanced Word Embedding (QL, SS, XL, AN, RF), pp. 2429–2432.
CIKM-2016-SoleimaniM #documentation #modelling #multi #topic: Semi-supervised Multi-Label Topic Models for Document Classification and Sentence Labeling (HS, DJM0), pp. 105–114.
CIKM-2016-WangTAL #documentation: Linked Document Embedding for Classification (SW, JT, CCA, HL0), pp. 115–124.
CIKM-2016-XuYLH: Cross-lingual Text Classification via Model Translation with Limited Dictionaries (RX, YY, HL, AH), pp. 95–104.
CIKM-2016-ZhangDH #ambiguity #case study #online #using: Bayesian Non-Exhaustive Classification A Case Study: Online Name Disambiguation using Temporal Record Streams (BZ, MD, MAH), pp. 1341–1350.
CIKM-2016-ZhangYZZ #matrix #network: Collective Classification via Discriminative Matrix Factorization on Sparsely Labeled Networks (DZ, JY, XZ, CZ), pp. 1563–1572.
CIKM-2016-ZhengC #constraints #learning #probability: Regularizing Structured Classifier with Conditional Probabilistic Constraints for Semi-supervised Learning (VWZ, KCCC), pp. 1029–1038.
ECIR-2016-BalikasA #multi #using: Multi-label, Multi-class Classification Using Polylingual Embeddings (GB, MRA), pp. 723–728.
ICML-2016-BaiRWS #difference #geometry #learning: Differential Geometric Regularization for Supervised Learning of Classifiers (QB, SR, ZW, SS), pp. 1879–1888.
ICML-2016-FernandoG #learning #video: Learning End-to-end Video Classification with Rank-Pooling (BF, SG), pp. 1187–1196.
ICML-2016-KantchelianTJ: Evasion and Hardening of Tree Ensemble Classifiers (AK, JDT, ADJ), pp. 2387–2396.
ICML-2016-LiWPA #multi: Conditional Bernoulli Mixtures for Multi-label Classification (CL, BW, VP, JAA), pp. 2482–2491.
ICML-2016-MartinsA #multi: From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification (AFTM, RFA), pp. 1614–1623.
ICML-2016-NatarajanKRD #multi: Optimal Classification with Multivariate Losses (NN, OK, PR, ISD), pp. 1530–1538.
ICML-2016-OkOSY #crowdsourcing: Optimality of Belief Propagation for Crowdsourced Classification (JO, SO, JS, YY), pp. 535–544.
ICML-2016-SuhZA #complexity: The Label Complexity of Mixed-Initiative Classifier Training (JS, XZ0, SA), pp. 2800–2809.
ICML-2016-YenHRZD #approach #multi: PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification (IEHY, XH, PR, KZ, ISD), pp. 3069–3077.
ICML-2016-ZhangLL #image #network #scalability: Augmenting Supervised Neural Networks with Unsupervised Objectives for Large-scale Image Classification (YZ, KL, HL), pp. 612–621.
ICPR-2016-AgarwalSV: Fingerprint sensor classification via Mélange of handcrafted features (AA0, RS0, MV), pp. 3001–3006.
ICPR-2016-AmeurVC #recognition: Sub-classification strategies for tree species recognition (RBA, LV, DC), pp. 2139–2144.
ICPR-2016-BaiCWJ0H #clustering #graph #kernel: Shape classification with a vertex clustering graph kernel (LB0, LC, YW0, XJ0, XB0, ERH), pp. 2634–2639.
ICPR-2016-BarddalGBE #benchmark #data type #metric: A benchmark of classifiers on feature drifting data streams (JPB, HMG, AdSBJ, FE), pp. 2180–2185.
ICPR-2016-BayramogluKH #image #independence #learning: Deep learning for magnification independent breast cancer histopathology image classification (NB, JK, JH), pp. 2440–2445.
ICPR-2016-Brandtberg #analysis #fourier #fuzzy #multi #order #rank #using: Virtual hexagonal and multi-scale operator for fuzzy rank order texture classification using one-dimensional generalised Fourier analysis (TB), pp. 2018–2024.
ICPR-2016-BSSH #approach #network #using: HEp-2 cell classification using artificial neural network approach (DB, KS, NH), pp. 84–89.
ICPR-2016-CorbelliBGC #analysis #documentation #layout: Historical document digitization through layout analysis and deep content classification (AC, LB, CG, RC), pp. 4077–4082.
ICPR-2016-DaoodRB #multi #recognition #using: Pollen recognition using a multi-layer hierarchical classifier (AD, ER, MB), pp. 3091–3096.
ICPR-2016-DasguptaN #fine-grained #multi: Leveraging multiple tasks to regularize fine-grained classification (RD, AMN), pp. 3476–3481.
ICPR-2016-DubosBAS: ROC-based cost-sensitive classification with a reject option (CD, SB, SA, RS), pp. 3320–3325.
ICPR-2016-FioriMF #design #multi: An optimal multiclass classifier design (MF, MDM, AF), pp. 480–485.
ICPR-2016-GonzalezVT #invariant #learning: Learning rotation invariant convolutional filters for texture classification (DM, MV, DT), pp. 2012–2017.
ICPR-2016-GoswamiRSV #normalisation: Improving classifier fusion via Pool Adjacent Violators normalization (GG, NKR, RS0, MV), pp. 1011–1016.
ICPR-2016-GrimmMBS #using: Sleep position classification from a depth camera using Bed Aligned Maps (TG, MM, AB, RS), pp. 319–324.
ICPR-2016-HasegawaH #image #named #network #using: PLSNet: A simple network using Partial Least Squares regression for image classification (RH, KH), pp. 1601–1606.
ICPR-2016-HouXX0 #graph #learning: Semi-supervised learning competence of classifiers based on graph for dynamic classifier selection (CH, YX, ZX, JS0), pp. 3650–3654.
ICPR-2016-HuangYZZ #reduction #robust: Rough Neighborhood Covering Reduction for robust classification (WH, XY, CZ, NZ), pp. 3308–3313.
ICPR-2016-IshiiSIMSIN #detection #multi: Detection by classification of buildings in multispectral satellite imagery (TI, ESS, SI, YM, AS, HI0, RN), pp. 3344–3349.
ICPR-2016-JamesC #social #social media: Evolutionary data purification for social media classification (SJ, JPC), pp. 2676–2681.
ICPR-2016-JiaSZY #network: Deep convolutional neural network based HEp-2 cell classification (XJ, LS, XZ, SY), pp. 77–80.
ICPR-2016-Julca-AguilarHM: Subexpression and dominant symbol histograms for spatial relation classification in mathematical expressions (FDJA, NSTH, HM, CVG), pp. 3446–3451.
ICPR-2016-KawanishiDIMF #learning #robust: Misclassification tolerable learning for robust pedestrian orientation classification (YK, DD, II, HM, HF), pp. 486–491.
ICPR-2016-KhareSKCLB #metric #quality #video: A quad tree based method for blurred and non-blurred video text frames classification through quality metrics (VK, PS, AK, CSC, TL, MB), pp. 4023–4028.
ICPR-2016-KimuraKSK #multi #performance #random #scalability: Fast random k-labELsets for large-scale multi-label classification (KK, MK, LS, SK), pp. 438–443.
ICPR-2016-KimV #semantics #using: Deep Action Unit classification using a binned intensity loss and semantic context model (EK, SV), pp. 4136–4141.
ICPR-2016-KrijtheL16a: Optimistic semi-supervised least squares classification (JHK, ML), pp. 1677–1682.
ICPR-2016-LangenkamperN #architecture #detection #learning #online #realtime: COATL - a learning architecture for online real-time detection and classification assistance for environmental data (DL, TWN), pp. 597–602.
ICPR-2016-LiaoLL #multi #network #robust #using: Skin disease classification versus skin lesion characterization: Achieving robust diagnosis using multi-label deep neural networks (HL, YL, JL), pp. 355–360.
ICPR-2016-LiHZXZ: HEp-2 specimen classification via deep CNNs and pattern histogram (HL0, HH, WSZ, XX, JZ), pp. 2145–2149.
ICPR-2016-LiSZY #network: HEp-2 specimen classification with fully convolutional network (YL, LS, XZ, SY), pp. 96–100.
ICPR-2016-Liu16a #learning #multi #network #scalability: Hierarchical learning for large multi-class network classification (LL), pp. 2307–2312.
ICPR-2016-LiuKWK #recognition #word: Scene text recognition with CNN classifier and WFST-based word labeling (XL, TK, XW, KK), pp. 3999–4004.
ICPR-2016-NguyenVPG: An integrated descriptor for texture classification (VLN, NSV, HHP, PHG), pp. 2006–2011.
ICPR-2016-NilssonO #complexity #pattern matching #pattern recognition #recognition: Estimates of Classification Complexity for Myoelectric Pattern Recognition (NN, MOC), pp. 2682–2687.
ICPR-2016-NookaCVSP #adaptation #network: Adaptive hierarchical classification networks (SPN, SC, KV, SS, RWP), pp. 3578–3583.
ICPR-2016-NorooziMNEA #predict #recognition: Fusion of classifier predictions for audio-visual emotion recognition (FN, MM, AN, SE, GA), pp. 61–66.
ICPR-2016-Norov-ErdeneKSK #locality #multi #problem: Locality in multi-label classification problems (BNE, MK, LS, KK), pp. 2319–2324.
ICPR-2016-OliveauS #image #semantics: Semantic-free attributes for image classification (QO, HS), pp. 1577–1582.
ICPR-2016-PrasathKOGHSP #random #segmentation #using: HEp-2 cell classification and segmentation using motif texture patterns and spatial features with random forests (VBSP, YMK, ZAO, JBG, AH, GS, KP), pp. 90–95.
ICPR-2016-PreslesD #invariant: A distance-based shape descriptor invariant to similitude and its application to shape classification (BP, JD), pp. 2598–2603.
ICPR-2016-RiabchenkoMAITG #fine-grained: Learned vs. engineered features for fine-grained classification of aquatic macroinvertebrates (ER, KM, IA0, AI, VT, MG, SK), pp. 2276–2281.
ICPR-2016-RoyCSC #predict: Meta-regression based pool size prediction scheme for dynamic selection of classifiers (AR, RMOC, RS, GDCC), pp. 216–221.
ICPR-2016-RoyDB #documentation #image #network: Generalized stacking of layerwise-trained Deep Convolutional Neural Networks for document image classification (SR, AD, UB), pp. 1273–1278.
ICPR-2016-SinoaraRR #semantics: Semantic role-based representations in text classification (RAS, RGR, SOR), pp. 2313–2318.
ICPR-2016-SunKK #multi: Multi-label classification with meta-label-specific features (LS, MK, KK), pp. 1612–1617.
ICPR-2016-TocaPC: AutoMarkov DNNs for object classification (CT, CP, MC), pp. 3452–3457.
ICPR-2016-Troya-GalvisGB #analysis #collaboration #image #segmentation: Collaborative segmentation and classification for remote sensing image analysis (ATG, PG, LBÉ), pp. 829–834.
ICPR-2016-VoTPV #detection #modelling: Model-based classification and novelty detection for point pattern data (BNV, NQT, DQP, BTV), pp. 2622–2627.
ICPR-2016-WangHG #learning #novel: A novel fingerprint classification method based on deep learning (RW, CH, TG), pp. 931–936.
ICPR-2016-WangTLW #representation #robust: Information-theoretic atomic representation for robust pattern classification (YW, YYT, LL, PSPW), pp. 3685–3690.
ICPR-2016-WangZYP #detection: Anomaly detection in crowded scenes by SL-HOF descriptor and foreground classification (SW, EZ, JY, FP), pp. 3398–3403.
ICPR-2016-Williams #network #using: Underwater target classification in synthetic aperture sonar imagery using deep convolutional neural networks (DPW), pp. 2497–2502.
ICPR-2016-WimmerUH #novel: A novel filterbank especially designed for the classification of colonic polyps (GW, AU, MH), pp. 2150–2155.
ICPR-2016-YeZL #documentation #network #online #random: Joint training of conditional random fields and neural networks for stroke classification in online handwritten documents (JYY, YMZ, CLL), pp. 3264–3269.
ICPR-2016-YildizU #incremental #order #using: Incremental construction of rule ensembles using classifiers produced by different class orderings (OTY, AU), pp. 492–497.
ICPR-2016-ZhaoSJ #identification #robust: Robust signal identification for dynamic pattern classification (RZ, GS, QJ), pp. 3910–3915.
ICPR-2016-ZhongGS: A DBN-crf for spectral-spatial classification of hyperspectral data (PZ0, ZG, CBS), pp. 1219–1224.
KDD-2016-ChiangLL #coordination #linear #manycore #parallel #scalability: Parallel Dual Coordinate Descent Method for Large-scale Linear Classification in Multi-core Environments (WLC, MCL, CJL), pp. 1485–1494.
KDD-2016-NandanwarM #network: Structural Neighborhood Based Classification of Nodes in a Network (SN, MNM), pp. 1085–1094.
KDD-2016-Ribeiro0G #predict #quote #trust #why: “Why Should I Trust You?”: Explaining the Predictions of Any Classifier (MTR, SS0, CG), pp. 1135–1144.
ECMFA-2016-AtkinsonK #ontology: Demystifying Ontological Classification in Language Engineering (CA, TK), pp. 83–100.
ASE-2016-WangWCW #crowdsourcing #testing: Local-based active classification of test report to assist crowdsourced testing (JW, SW, QC, QW), pp. 190–201.
FSE-2016-PanichellaSGVCG #development #named: ARdoc: app reviews development oriented classifier (SP, ADS, EG, CAV, GC, HCG), pp. 1023–1027.
ICSE-2016-FavaSOSW #crowdsourcing #game studies: Crowdsourcing program preconditions via a classification game (DF, DS, JCO, MS, EJWJ), pp. 1086–1096.
ICSE-2016-Tantithamthavorn #automation #fault #modelling #optimisation #parametricity #predict: Automated parameter optimization of classification techniques for defect prediction models (CT, SM, AEH, KM), pp. 321–332.
ICSE-2016-ZhangZZH #fault #predict #using: Cross-project defect prediction using a connectivity-based unsupervised classifier (FZ0, QZ, YZ0, AEH), pp. 309–320.
ASPLOS-2016-MukkaraBS #named: Whirlpool: Improving Dynamic Cache Management with Static Data Classification (AM, NB, DS0), pp. 113–127.
CASE-2016-ChenKZW #algorithm #clustering #novel: A novel under-sampling algorithm based on Iterative-Partitioning Filters for imbalanced classification (XC, QK, MZ, ZW), pp. 490–494.
CASE-2016-SharabianiSD #novel #representation: A novel Bayesian and Chain Rule Model on symbolic representation for time series classification (AS, AS, HD), pp. 1014–1019.
CASE-2016-SussD #behaviour #component #performance #simulation: Classification of mechatronic components for efficient plant behaviour simulation (SS, CD), pp. 1146–1151.
DocEng-2015-FerreiraLCFSR #automation #documentation #summary #using: Automatic Document Classification using Summarization Strategies (RF, RDL, LdSC, FF, SJS, MR), pp. 69–72.
DocEng-2015-SvendsenA #documentation: Change Classification in Graphics-Intensive Digital Documents (JS, ABA), pp. 203–206.
HT-2015-BurnapCS #analysis #communication #twitter: Machine Classification and Analysis of Suicide-Related Communication on Twitter (PB, WC, JS), pp. 75–84.
EDM-2015-EmondB #process #sequence #student #using: Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification (BE, SB), pp. 412–415.
EDM-2015-LuoK0 #performance #predict #student: Discrimination-Aware Classifiers for Student Performance Prediction (LL, IK, WL0), pp. 384–387.
EDM-2015-SameiRNM #online: Hierarchical Dialogue Act Classification in Online Tutoring Sessions (BS, VR, BN, DMM), pp. 600–601.
EDM-2015-StrechtCSMA #algorithm #case study #comparative #modelling #performance #student: A Comparative Study of Regression and Classification Algorithms for Modelling Students' Academic Performance (PS, LC0, CS, JMM, RA), pp. 392–395.
MSR-2015-OhiraKYYMLFHIM #dataset #debugging: A Dataset of High Impact Bugs: Manually-Classified Issue Reports (MO, YK, YY, HY, YM, NL, KF, HH, AI, KiM), pp. 518–521.
CHI-PLAY-2015-HeintzL #game studies: The Game Genre Map: A Revised Game Classification (SH, ELCL), pp. 175–184.
VS-Games-2015-BalducciGC #design #game studies: Classification of Affective Data to Evaluate the Level Design in a Role-Playing Videogame (FB, CG, RC), pp. 1–8.
CHI-2015-FaircloughKG #interactive #realtime: Classification Accuracy from the Perspective of the User: Real-Time Interaction with Physiological Computing (SHF, AJK, KMG), pp. 3029–3038.
CHI-2015-KayPK #evaluation #how #overview: How Good is 85%?: A Survey Tool to Connect Classifier Evaluation to Acceptability of Accuracy (MK, SNP, JAK), pp. 347–356.
CHI-2015-SatoYOSHTHR #interactive #named: SpecTrans: Versatile Material Classification for Interaction with Textureless, Specular and Transparent Surfaces (MS, SY, AO, BS, AH, TT, MH, RR), pp. 2191–2200.
CSCW-2015-ChengB #hybrid #machine learning #named: Flock: Hybrid Crowd-Machine Learning Classifiers (JC, MSB), pp. 600–611.
HCI-IT-2015-SatoAOO #analysis #automation #image: Automatic Classification Between Involuntary and Two Types of Voluntary Blinks Based on an Image Analysis (HS, KA, SO, MO), pp. 140–149.
HIMI-IKD-2015-KastratiIY #documentation #framework #using: A General Framework for Text Document Classification Using SEMCON and ACVSR (ZK, ASI, SYY), pp. 310–319.
ICEIS-v1-2015-FerrandinENSA #approach: A Centroid-based Approach for Hierarchical Classification (MF, FE, JCN, EES, BCÁ), pp. 25–33.
ICEIS-v1-2015-PfaffK #automation #benchmark #documentation #identification #metric #natural language: Natural Language Processing Techniques for Document Classification in IT Benchmarking — Automated Identification of Domain Specific Terms (MP, HK), pp. 360–366.
ICEIS-v1-2015-SunB #mining #process: Function-based Case Classification for Improving Business Process Mining (YS, BB), pp. 251–258.
CIKM-2015-AiWSYZC #multi: Best First Over-Sampling for Multilabel Classification (XA, JW0, VSS, YY, PZ, ZC), pp. 1803–1806.
CIKM-2015-BerardiEMO0 #automation #identification: Semi-Automated Text Classification for Sensitivity Identification (GB, AE, CM, IO, FS0), pp. 1711–1714.
CIKM-2015-GuiLXLW #estimation #novel: A Novel Class Noise Estimation Method and Application in Classification (LG0, QL0, RX, ML, QW), pp. 1081–1090.
CIKM-2015-HongWW #clustering #learning: Clustering-based Active Learning on Sensor Type Classification in Buildings (DH, HW, KW), pp. 363–372.
CIKM-2015-JinZPDLH #learning #multi #semantics: Heterogeneous Multi-task Semantic Feature Learning for Classification (XJ0, FZ, SJP, CD, PL0, QH), pp. 1847–1850.
CIKM-2015-KhudaBukhshBW #case study #detection #effectiveness #query #self: Building Effective Query Classifiers: A Case Study in Self-harm Intent Detection (ARK, PNB, RWW), pp. 1735–1738.
CIKM-2015-LiZ #statistics: Associative Classification with Statistically Significant Positive and Negative Rules (JL, ORZ), pp. 633–642.
CIKM-2015-RudraGGGG #approach #microblog: Extracting Situational Information from Microblogs during Disaster Events: a Classification-Summarization Approach (KR, SG, NG, PG, SG0), pp. 583–592.
CIKM-2015-ViegasGMR #documentation #effectiveness #lazy evaluation #naive bayes #parallel #performance: Parallel Lazy Semi-Naive Bayes Strategies for Effective and Efficient Document Classification (FV, MAG, WM, LCdR), pp. 1071–1080.
CIKM-2015-WangZTCZ #graph: Defragging Subgraph Features for Graph Classification (HW, PZ0, IWT, LC0, CZ), pp. 1687–1690.
CIKM-2015-WanLKYGCH #learning #network: Classification with Active Learning and Meta-Paths in Heterogeneous Information Networks (CW, XL, BK, XY, QG, DWLC, JH0), pp. 443–452.
CIKM-2015-YangZ #framework #graph #online #optimisation: A Min-Max Optimization Framework For Online Graph Classification (PY, PZ), pp. 643–652.
ECIR-2015-CanneytCD #sentiment #topic #twitter: Topic-Dependent Sentiment Classification on Twitter (SVC, NC, BD), pp. 441–446.
ECIR-2015-EfremovaGC: Classification of Historical Notary Acts with Noisy Labels (JE, AMG, TC), pp. 49–54.
ECIR-2015-HagenPBS #detection #sentiment #twitter #using: Twitter Sentiment Detection via Ensemble Classification Using Averaged Confidence Scores (MH, MP, MB, BS), pp. 741–754.
ECIR-2015-RomeoIT #documentation #knowledge-based #multi #representation: Knowledge-Based Representation for Transductive Multilingual Document Classification (SR, DI, AT), pp. 92–103.
ECIR-2015-SaracIGD #concept #flexibility #framework #named: ConceptFusion: A Flexible Scene Classification Framework (MIS, AI, EG, PD), pp. 55–60.
ECIR-2015-SchindlerR #approach #music: An Audio-Visual Approach to Music Genre Classification through Affective Color Features (AS, AR), pp. 61–67.
ICML-2015-GasseAE #composition #multi #on the #set: On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property (MG, AA, HE), pp. 2531–2539.
ICML-2015-HazanLM #rank: Classification with Low Rank and Missing Data (EH, RL, YM), pp. 257–266.
ICML-2015-HuangWSLC #image #learning #metric #set #symmetry: Log-Euclidean Metric Learning on Symmetric Positive Definite Manifold with Application to Image Set Classification (ZH, RW, SS, XL, XC), pp. 720–729.
ICML-2015-OsadchyHK: K-hyperplane Hinge-Minimax Classifier (MO, TH, DK), pp. 1558–1566.
ICML-2015-RamaswamyT0: Convex Calibrated Surrogates for Hierarchical Classification (HGR, AT, SA), pp. 1852–1860.
ICML-2015-RichmanM #constraints: Dynamic Sensing: Better Classification under Acquisition Constraints (OR, SM), pp. 267–275.
KDD-2015-BifetMRHP #big data #data type #evaluation #online #performance: Efficient Online Evaluation of Big Data Stream Classifiers (AB, GDFM, JR, GH, BP), pp. 59–68.
KDD-2015-ChakrabortyBSPY #framework #learning #named #novel: BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification (SC, VNB, ARS, SP, JY), pp. 99–108.
KDD-2015-ChuHTLL #linear #parametricity: Warm Start for Parameter Selection of Linear Classifiers (BYC, CHH, CHT, CYL, CJL), pp. 149–158.
KDD-2015-OkumuraST #analysis #incremental #linear #problem: Quick Sensitivity Analysis for Incremental Data Modification and Its Application to Leave-one-out CV in Linear Classification Problems (SO, YS, IT), pp. 885–894.
KDD-2015-RoyTZLHNM: Dynamic Hierarchical Classification for Patient Risk-of-Readmission (SBR, AT, KZ, RL, DH, SN, AM), pp. 1691–1700.
KDD-2015-SethiYRVR #machine learning #scalability #using: Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing Imagery (MS, YY, AR, RRV, SR), pp. 2069–2078.
KDD-2015-SunAYMMBY #learning: Transfer Learning for Bilingual Content Classification (QS, MSA, BY, CM, VM, AB, JY), pp. 2147–2156.
MLDM-2015-Babu #identification #using: Offline Writer Identification in Tamil Using Bagged Classification Trees (SB), pp. 342–354.
MLDM-2015-DavidsenSP #fuzzy #search-based: Local and Global Genetic Fuzzy Pattern Classifiers (SAD, ES, MP), pp. 55–69.
MLDM-2015-Prado #named: MOGACAR: A Method for Filtering Interesting Classification Association Rules (DBP), pp. 172–183.
SEKE-2015-TaheriS #agile #development: A Feature-Based Tool-Selection Classification for Agile Software Development (MT, SMS), pp. 700–704.
SEKE-2015-YangL #identification #requirements: Identification and Classification of Requirements from App User Reviews (HY, PL), pp. 7–12.
SIGIR-2015-CanutoGSRM #approach #documentation #parallel #performance #scalability: An Efficient and Scalable MetaFeature-based Document Classification Approach based on Massively Parallel Computing (SDC, MAG, WS, TR, WM), pp. 333–342.
SIGIR-2015-EswaranBP #modelling #scalability #topic: Modeling Website Topic Cohesion at Scale to Improve Webpage Classification (DE, PNB, JJPI), pp. 787–790.
SIGIR-2015-FangOHML #topic #twitter: Topic-centric Classification of Twitter User’s Political Orientation (AF, IO, PH, CM, NL), pp. 791–794.
SIGIR-2015-SallesGRR #automation #effectiveness #fault #named #random: BROOF: Exploiting Out-of-Bag Errors, Boosting and Random Forests for Effective Automated Classification (TS, MAG, VR, LCdR), pp. 353–362.
ASE-2015-ChoetkiertikulD #predict #using: Predicting Delays in Software Projects Using Networked Classification (T) (MC, HKD, TT, AG), pp. 353–364.
ASE-2015-GuzmanEB #approach #evolution #overview: Ensemble Methods for App Review Classification: An Approach for Software Evolution (N) (EG, MEH, BB), pp. 771–776.
ICSE-v1-2015-GhotraMH #fault #modelling #performance #predict: Revisiting the Impact of Classification Techniques on the Performance of Defect Prediction Models (BG, SM, AEH), pp. 789–800.
ICSE-v1-2015-PetrosyanRM #api #information management #using: Discovering Information Explaining API Types Using Text Classification (GP, MPR, RDM), pp. 869–879.
SAC-2015-BerardiEF0 #mobile #multi: Multi-store metadata-based supervised mobile app classification (GB, AE, TF, FS), pp. 585–588.
SAC-2015-BurkhardtK #multi #on the: On the spectrum between binary relevance and classifier chains in multi-label classification (SB, SK), pp. 885–892.
SAC-2015-CharuvakaR #approximate #coordination #scalability: Approximate block coordinate descent for large scale hierarchical classification (AC, HR), pp. 837–844.
SAC-2015-GomesBE #data type #learning: Pairwise combination of classifiers for ensemble learning on data streams (HMG, JPB, FE), pp. 941–946.
SAC-2015-GonzalezRP #image: Computationally-efficient classification of HEp-2 cell patterns in IIF images (LFPG, DDAR, MSP), pp. 825–830.
SAC-2015-MakrisVV #predict: Classification model for predicting cost slippage in governmental ICT projects (CM, PV, JV), pp. 1238–1241.
SAC-2015-OmatuYI #learning #smell: Smell classification of wines by the learning vector quantization method (SO, MY, YI), pp. 195–200.
SAC-2015-RochaRCOMVADGF #algorithm #dataset #documentation #named #performance #using: G-KNN: an efficient document classification algorithm for sparse datasets on GPUs using KNN (LCdR, GSR, RC, RSO, DM, FV, GA, SD, MAG, RF), pp. 1335–1338.
SAC-2015-TakemuraTT #twitter: Classification of Twitter follow links based on the followers’ intention (HT, AT, KT), pp. 1174–1180.
DAC-2015-ChenCX #named #power management #video: DaTuM: dynamic tone mapping technique for OLED display power saving based on video classification (XC, YC, CJX), p. 6.
DAC-2015-VenkataramaniRL #energy #machine learning: Scalable-effort classifiers for energy-efficient machine learning (SV, AR, JL, MS), p. 6.
DATE-2015-OyaSYT #identification: A score-based classification method for identifying hardware-trojans at gate-level netlists (MO, YS, MY, NT), pp. 465–470.
HPCA-2015-RosDK #clustering #performance: Hierarchical private/shared classification: The key to simple and efficient coherence for clustered cache hierarchies (AR, MD, SK), pp. 186–197.
ISSTA-2015-XueWLXSC #behaviour #detection #javascript #modelling: Detection and classification of malicious JavaScript via attack behavior modelling (YX, JW, YL, HX, JS, MC), pp. 48–59.
DocEng-2014-DiemKS #analysis #documentation: Ruling analysis and classification of torn documents (MD, FK, RS), pp. 63–72.
DRR-2014-KleberDS #retrieval #using #word: Form classification and retrieval using bag of words with shape features of line structures (FK, MD, RS), pp. 902107–9.
DRR-2014-YouADT #image #retrieval: A contour-based shape descriptor for biomedical image classification and retrieval (DY, SA, DDF, GRT), p. ?–12.
HT-2014-TanakaTT #twitter #why: Why you follow: a classification scheme for twitter follow links (AT, HT, KT), pp. 324–326.
JCDL-2014-ChoiLD #automation #using #what: What is this song about anyway?: Automatic classification of subject using user interpretations and lyrics (KC, JHL, JSD), pp. 453–454.
JCDL-2014-TakanoSIHT #analysis #behaviour #documentation #towards: Microscopic analysis of document handling while reading: Classification of behavior toward paper document (KT, HS, JI, TH, ST), pp. 445–446.
VLDB-2014-SunRYD #crowdsourcing #machine learning #named #scalability #using: Chimera: Large-Scale Classification using Machine Learning, Rules, and Crowdsourcing (CS, NR, FY, AD), pp. 1529–1540.
VLDB-2014-YuYWLC #big data #design #detection #power management: Big Data Small Footprint: The Design of A Low-Power Classifier for Detecting Transportation Modes (MCY, TY, SCW, CJL, EYC), pp. 1429–1440.
EDM-2014-Ezen-CanB14a: A Preliminary Investigation of Learner Characteristics for Unsupervised Dialogue Act Classification (AEC, KEB), pp. 373–374.
EDM-2014-SilvaPC #predict #video: A Predictive Model for Video Lectures Classification (PS, RP, EC), pp. 325–326.
ITiCSE-2014-TedreBMC #concept #education #identification #towards: Towards identification and classification of core and threshold concepts in methodology education in computing (MT, DB, SMB, JCC), pp. 237–242.
ICPC-2014-ThungLOC #design #diagrams #metric #network #using: Condensing class diagrams by analyzing design and network metrics using optimistic classification (FT, DL, MHO, MRVC), pp. 110–121.
ICSME-2014-ZhouTGG #data mining #debugging #mining: Combining Text Mining and Data Mining for Bug Report Classification (YZ, YT, RG, HCG), pp. 311–320.
MSR-2014-KochharLL #debugging #locality #question: It’s not a bug, it’s a feature: does misclassification affect bug localization? (PSK, TDBL, DL), pp. 296–299.
CHI-2014-LiuCBLM #navigation: Effects of display size and navigation type on a classification task (CL, OC, MBL, EL, WEM), pp. 4147–4156.
CHI-2014-SchwarzXMHH #probability #using: Probabilistic palm rejection using spatiotemporal touch features and iterative classification (JS, RX, JM, SEH, CH), pp. 2009–2012.
CSCW-2014-MillerGS #collaboration #visualisation: Unsupervised classification and visualization of unstructured text for the support of interdisciplinary collaboration (LJM, RG, SS), pp. 1033–1042.
DHM-2014-IkenoboKKTG: The Classification Tendency and Common Denomination of the Points Paid Attention in Ikebana Instruction (YI, NK, NK, YT, AG), pp. 263–272.
HIMI-DE-2014-Banic #interactive #visualisation: Selection Classification for Interaction with Immersive Volumetric Visualizations (AUB), pp. 10–21.
LCT-NLE-2014-TaraghiSES #learning #markov #multi: Markov Chain and Classification of Difficulty Levels Enhances the Learning Path in One Digit Multiplication (BT, AS, ME, MS), pp. 322–333.
SCSM-2014-MendesFFC #analysis #how #social #using: How Do Users Express Their Emotions Regarding the Social System in Use? A Classification of Their Postings by Using the Emotional Analysis of Norman (MSM, EF, VF, MFdC), pp. 229–241.
VISSOFT-2014-DanielWSSL #dependence #named #visualisation: Polyptychon: A Hierarchically-Constrained Classified Dependencies Visualization (DTD, EW, KS, MS, PL), pp. 83–86.
ICEIS-v1-2014-0001DFL #constraints #documentation #process: Service Level Agreement Constraints into Processes for Document Classification (MB, MD, FF, AL), pp. 545–550.
CIKM-2014-CanutoSGRRGRM #effectiveness #on the #performance: On Efficient Meta-Level Features for Effective Text Classification (SDC, TS, MAG, LCdR, GSR, LG, TCR, WSM), pp. 1709–1718.
CIKM-2014-ChanDYTZ #ranking #retrieval: Term Selection and Result Reranking for Question Retrieval by Exploiting Hierarchical Classification (WC, JD, WY, JT, XZ), pp. 141–150.
CIKM-2014-HanWP #using: Within-Network Classification Using Radius-Constrained Neighborhood Patterns (JH, JRW, JP), pp. 1539–1548.
CIKM-2014-HongBH #framework #multi: A Mixtures-of-Trees Framework for Multi-Label Classification (CH, IB, MH), pp. 211–220.
CIKM-2014-LinLYC #modelling #sentiment: Exploring Ensemble of Models in Taxonomy-based Cross-Domain Sentiment Classification (CKL, YYL, CHY, HHC), pp. 1279–1288.
CIKM-2014-LiuLK #information management #performance #using: Using Local Information to Significantly Improve Classification Performance (WL, DL, RK), pp. 1947–1950.
CIKM-2014-LiZLW #probability: Probabilistic Classifier Chain Inference via Gibbs Sampling (LL, LZ, GL, HW), pp. 1855–1858.
CIKM-2014-LuciaF #knowledge-based #named #network: EgoCentric: Ego Networks for Knowledge-based Short Text Classification (WL, EF), pp. 1079–1088.
CIKM-2014-MaoWHO #learning #linear #multi: Nonlinear Classification via Linear SVMs and Multi-Task Learning (XM, OW, WH, PO), pp. 1955–1958.
CIKM-2014-WangWLW #concept #ranking: Concept-based Short Text Classification and Ranking (FW, ZW, ZL, JRW), pp. 1069–1078.
ECIR-2014-KimJHLY #automation: Quality-Based Automatic Classification for Presentation Slides (SK, WJ, KH, JGL, MYY), pp. 638–643.
ECIR-2014-LuoGWL #algorithm #named #network #novel: HetPathMine: A Novel Transductive Classification Algorithm on Heterogeneous Information Networks (CL, RG, ZW, CL), pp. 210–221.
ECIR-2014-McDonaldMOG #overview #perspective #towards: Towards a Classifier for Digital Sensitivity Review (GM, CM, IO, TG), pp. 500–506.
ICML-c1-2014-LiL #multi: Condensed Filter Tree for Cost-Sensitive Multi-Label Classification (CLL, HTL), pp. 423–431.
ICML-c1-2014-YangSX: The Coherent Loss Function for Classification (WY, MS, HX), pp. 37–45.
ICML-c2-2014-BaiLS #framework #online: A Bayesian Framework for Online Classifier Ensemble (QB, HL, SS), pp. 1584–1592.
ICML-c2-2014-EbanMG: Discrete Chebyshev Classifiers (EE, EM, AG), pp. 1233–1241.
ICML-c2-2014-LiG #learning #representation #semantics: Latent Semantic Representation Learning for Scene Classification (XL, YG), pp. 532–540.
ICML-c2-2014-LinDH0 #encoding #multi: Multi-label Classification via Feature-aware Implicit Label Space Encoding (ZL, GD, MH, JW), pp. 325–333.
ICML-c2-2014-RodriguesPR #learning #multi #process: Gaussian Process Classification and Active Learning with Multiple Annotators (FR, FCP, BR), pp. 433–441.
ICML-c2-2014-SunIM #learning #linear: Learning Mixtures of Linear Classifiers (YS, SI, AM), pp. 721–729.
ICPR-2014-AliNB #constraints #image #probability #scalability: Boosting Stochastic Newton with Entropy Constraint for Large-Scale Image Classification (WBHA, RN, MB), pp. 232–237.
ICPR-2014-AndreuLMG #analysis #automation #gender #image: Analysis of the Effect of Image Resolution on Automatic Face Gender Classification (YA, JLC, RAM, PGS), pp. 273–278.
ICPR-2014-BagheriGE #approach #novel #subclass: Generic Subclass Ensemble: A Novel Approach to Ensemble Classification (MAB, QG, SE), pp. 1254–1259.
ICPR-2014-BagheriHGE #framework #multi #recognition: A Framework of Multi-classifier Fusion for Human Action Recognition (MAB, GH, QG, SE), pp. 1260–1265.
ICPR-2014-BanerjeeCM #automation #game studies #generative #wiki: Playscript Classification and Automatic Wikipedia Play Articles Generation (SB, CC, PM), pp. 3630–3635.
ICPR-2014-BargiXP #adaptation #infinity #learning #online #segmentation #streaming: An Infinite Adaptive Online Learning Model for Segmentation and Classification of Streaming Data (AB, RYDX, MP), pp. 3440–3445.
ICPR-2014-BhattacharyaGC #estimation: Test Point Specific k Estimation for kNN Classifier (GB, KG, ASC), pp. 1478–1483.
ICPR-2014-BougueliaBB #data type #detection #novel #performance: Efficient Active Novel Class Detection for Data Stream Classification (MRB, YB, AB), pp. 2826–2831.
ICPR-2014-BouillonA #evolution #gesture #learning #online: Supervision Strategies for the Online Learning of an Evolving Classifier for Gesture Commands (MB, ÉA), pp. 2029–2034.
ICPR-2014-ByeonLB #2d #network #using: Texture Classification Using 2D LSTM Networks (WB, ML, TMB), pp. 1144–1149.
ICPR-2014-CaoHS #approach #kernel #learning #multi: Optimization-Based Extreme Learning Machine with Multi-kernel Learning Approach for Classification (LlC, WbH, FS), pp. 3564–3569.
ICPR-2014-Cevikalp: 2-Sided Best Fitting Hyperplane Classifier (HC), pp. 226–231.
ICPR-2014-ChenCF #approach #hybrid #semantics: A Hybrid Holistic/Semantic Approach for Scene Classification (ZC, ZC, HF), pp. 2299–2304.
ICPR-2014-CheplyginaSTPLB #learning #multi: Classification of COPD with Multiple Instance Learning (VC, LS, DMJT, JJHP, ML, MdB), pp. 1508–1513.
ICPR-2014-CordellaSFF #random #reliability: Random Forest for Reliable Pre-classification of Handwritten Characters (LPC, CDS, FF, ASdF), pp. 1319–1324.
ICPR-2014-Dahllof: Scribe Attribution for Early Medieval Handwriting by Means of Letter Extraction and Classification and a Voting Procedure for Larger Pieces (MD), pp. 1910–1915.
ICPR-2014-DongPHLDJ #network #using: Vehicle Type Classification Using Unsupervised Convolutional Neural Network (ZD, MP, YH, TL, YD, YJ), pp. 172–177.
ICPR-2014-DornaikaBSR #encoding #graph #locality: Locality Constrained Encoding Graph Construction and Application to Outdoor Object Classification (FD, AB, HS, YR), pp. 2483–2488.
ICPR-2014-DuHZWD #case study #design #network #online #recognition #using: A Study of Designing Compact Classifiers Using Deep Neural Networks for Online Handwritten Chinese Character Recognition (JD, JSH, BZ, SW, LRD), pp. 2950–2955.
ICPR-2014-El-GaalyTE: Spatial-Visual Label Propagation for Local Feature Classification (TEG, MT, AME), pp. 3422–3427.
ICPR-2014-EnsafiLKT #automation #image: Automatic CAD System for HEp-2 Cell Image Classification (SE, SL, AAK, CLT), pp. 3321–3326.
ICPR-2014-FahadTR #clustering #process #recognition #smarttech #using: Activity Recognition in Smart Homes Using Clustering Based Classification (LGF, SFT, MR), pp. 1348–1353.
ICPR-2014-FangZ #learning: Cross Domain Shared Subspace Learning for Unsupervised Transfer Classification (ZF, ZZ), pp. 3927–3932.
ICPR-2014-Filippone #process #pseudo: Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC (MF), pp. 614–619.
ICPR-2014-GadermayrHU #adaptation: Scale-Adaptive Texture Classification (MG, SH, AU), pp. 2643–2648.
ICPR-2014-Garcia-OlallaAFG #statistics: Local Oriented Statistics Information Booster (LOSIB) for Texture Classification (OGO, EA, LFR, VGC), pp. 1114–1119.
ICPR-2014-GavriilidisT #kernel #random #using: Random Walk Kernel Applications to Classification Using Support Vector Machines (VG, AT), pp. 3898–3903.
ICPR-2014-Gonzalez-CastroDC #adaptation #using: Pixel Classification Using General Adaptive Neighborhood-Based Features (VGC, JD, VC), pp. 3750–3755.
ICPR-2014-HadjadjiCG #multi: Multiple One-Class Classifier Combination for Multi-class Classification (BH, YC, YG), pp. 2832–2837.
ICPR-2014-HafianePS #adaptation: Adaptive Median Binary Patterns for Texture Classification (AH, KP, GS), pp. 1138–1143.
ICPR-2014-HafnerLUW: Bridging the Resolution Gap between Endoscope Types for a Colonic Polyp Classification (MH, ML, AU, GW), pp. 2739–2744.
ICPR-2014-HavaeiJL #interactive #performance #segmentation: Efficient Interactive Brain Tumor Segmentation as Within-Brain kNN Classification (MH, PMJ, HL), pp. 556–561.
ICPR-2014-HazelhoffCW #trade-off #word: Optimal Performance-Efficiency Trade-off for Bag of Words Classification of Road Signs (LBH, IMC, PHNdW), pp. 2996–3001.
ICPR-2014-IosifidisTP #network: Semi-supervised Classification of Human Actions Based on Neural Networks (AI, AT, IP), pp. 1336–1341.
ICPR-2014-JangLSK #automation #multi #using #video: Automatic Video Genre Classification Using Multiple SVM Votes (WDJ, CL, JYS, CSK), pp. 2655–2660.
ICPR-2014-KangKYLD #documentation #image #network: Convolutional Neural Networks for Document Image Classification (LK, JK, PY, YL, DSD), pp. 3168–3172.
ICPR-2014-KrawczykWC #clustering #fuzzy: Weighted One-Class Classifier Ensemble Based on Fuzzy Feature Space Partitioning (BK, MW, BC), pp. 2838–2843.
ICPR-2014-LiDXWP #image #probability: Local Label Probability Propagation for Hyperspectral Image Classification (HL, JD, SX, LW, CP), pp. 4251–4256.
ICPR-2014-LiHYGPJ #re-engineering: Locality-Constrained Sparse Reconstruction for Trajectory Classification (CL, ZH, QY, SG, LP, JJ), pp. 2602–2606.
ICPR-2014-LiuCVC: Leaf Species Classification Based on a Botanical Shape Sub-classifier Strategy (HL, DC, LV, GC), pp. 1496–1501.
ICPR-2014-LiuL0L #image #learning: Regularized Hierarchical Feature Learning with Non-negative Sparsity and Selectivity for Image Classification (BL, JL, XB, HL), pp. 4293–4298.
ICPR-2014-LiYLYWH #multi #predict: Multi-view Based AdaBoost Classifier Ensemble for Class Prediction from Gene Expression Profiles (LL, ZY, JL, JY, HSW, GH), pp. 178–183.
ICPR-2014-LovatoMCGB #2d #biology #named #sequence: S-BLOSUM: Classification of 2D Shapes with Biological Sequence Alignment (PL, AM, CC, AG, MB), pp. 2335–2340.
ICPR-2014-McCarthyCO #image: The Contribution of Morphological Features in the Classification of Prostate Carcinoma in Digital Pathology Images (NM, PC, GO), pp. 3269–3273.
ICPR-2014-NeumannHKKB #image: Erosion Band Features for Cell Phone Image Based Plant Disease Classification (MN, LH, BK, KK, CB), pp. 3315–3320.
ICPR-2014-NguyenTHM #novel: A Novel Sphere-Based Maximum Margin Classification Method (PN, DT, XH, WM), pp. 620–624.
ICPR-2014-NocetiO #graph #kernel #process: A Spectral Graph Kernel and Its Application to Collective Activities Classification (NN, FO), pp. 3892–3897.
ICPR-2014-OuyedA #kernel: Feature Relevance for Kernel Logistic Regression and Application to Action Classification (OO, MSA), pp. 1325–1329.
ICPR-2014-PerinaKB #array #kernel #using: Expression Microarray Data Classification Using Counting Grids and Fisher Kernel (AP, MK, MB), pp. 1770–1775.
ICPR-2014-PillaiFR #learning #multi: Learning of Multilabel Classifiers (IP, GF, FR), pp. 3452–3456.
ICPR-2014-PistocchiCBFC #3d #detection #kernel: Kernelized Structural Classification for 3D Dogs Body Parts Detection (SP, SC, SB, NF, RC), pp. 1993–1998.
ICPR-2014-QianZX #multi #social: Boosted Multi-modal Supervised Latent Dirichlet Allocation for Social Event Classification (SQ, TZ, CX), pp. 1999–2004.
ICPR-2014-RahmaniMHM #linear: Action Classification with Locality-Constrained Linear Coding (HR, AM, DQH, ASM), pp. 3511–3516.
ICPR-2014-RavalTJ #encoding #evaluation #fault #performance #using: Efficient Evaluation of SVM Classifiers Using Error Space Encoding (NR, RVT, CVJ), pp. 4411–4416.
ICPR-2014-RengarajanRA #estimation #metric: Motion Estimation and Classification in Compressive Sensing from Dynamic Measurements (VR, ANR, RA), pp. 3475–3480.
ICPR-2014-RenYZH #image #learning #nearest neighbour: Learning Convolutional Nonlinear Features for K Nearest Neighbor Image Classification (WR, YY, JZ, KH), pp. 4358–4363.
ICPR-2014-SamantaC #using: Indian Classical Dance Classification on Manifold Using Jensen-Bregman LogDet Divergence (SS, BC), pp. 4507–4512.
ICPR-2014-SatoKSK #learning #multi: Learning Multiple Complex Features Based on Classification Results (YS, KK, YS, MK), pp. 3369–3373.
ICPR-2014-Saux #design #interactive: Interactive Design of Object Classifiers in Remote Sensing (BLS), pp. 2572–2577.
ICPR-2014-SicreJ #image: Discovering and Aligning Discriminative Mid-level Features for Image Classification (RS, FJ), pp. 1975–1980.
ICPR-2014-SlavkovikjVNHW: Image-Based Road Type Classification (VS, SV, WDN, SVH, RVdW), pp. 2359–2364.
ICPR-2014-SousaSB #case study #set: Time Series Transductive Classification on Imbalanced Data Sets: An Experimental Study (CARdS, VMAdS, GEAPAB), pp. 3780–3785.
ICPR-2014-SouzaSB: Extracting Texture Features for Time Series Classification (VMAdS, DFS, GEAPAB), pp. 1425–1430.
ICPR-2014-TabiaV #3d #using: 3D Shape Classification Using Information Fusion (HT, NSV), pp. 297–302.
ICPR-2014-TerissiPG #random #using: Lip Reading Using Wavelet-Based Features and Random Forests Classification (LDT, MP, JCG), pp. 791–796.
ICPR-2014-VilaltaGM #adaptation: Domain Adaptation under Data Misalignment: An Application to Cepheid Variable Star Classification (RV, KDG, LM), pp. 3660–3665.
ICPR-2014-WangT: Label-Denoising Auto-encoder for Classification with Inaccurate Supervision Information (DW, XT), pp. 3648–3653.
ICPR-2014-WenLWCW #feature model #robust: Optimal Feature Selection for Robust Classification via l2, 1-Norms Regularization (JW, ZL, WKW, JC, MW), pp. 517–521.
ICPR-2014-Xiang0L #hybrid #image: Local Hybrid Coding for Image Classification (WX, JW, ML), pp. 3744–3749.
ICPR-2014-XuSLPT #video: Graphics and Scene Text Classification in Video (JX, PS, TL, TQP, CLT), pp. 4714–4719.
ICPR-2014-XuSLT #2d #3d #video: 2D and 3D Video Scene Text Classification (JX, PS, TL, CLT), pp. 2932–2937.
ICPR-2014-YamashitaW #using: k-NN Classification of Handwritten Characters Using a New Distortion-Tolerant Matching Measure (YY, TW), pp. 262–267.
ICPR-2014-YangLTSG: Shape-Based Classification of Environmental Microorganisms (CY, CL, OT, KS, MG), pp. 3374–3379.
ICPR-2014-YanHCCC #representation: PLSA-Based Sparse Representation for Object Classification (YY, JWH, HFC, SCC, DYC), pp. 1295–1300.
ICPR-2014-YanSRLS #interactive #learning #multi: Evaluating Multi-task Learning for Multi-view Head-Pose Classification in Interactive Environments (YY, RS, ER, OL, NS), pp. 4182–4187.
ICPR-2014-YiMHP #invariant #locality #multi #process: Pose Invariant Activity Classification for Multi-floor Indoor Localization (SY, PWM, TKH, VP), pp. 3505–3510.
ICPR-2014-YinYPH #case study #learning: Shallow Classification or Deep Learning: An Experimental Study (XCY, CY, WYP, HWH), pp. 1904–1909.
ICPR-2014-YuanT #algorithm #image #multi: Multi-scale Tensor l1-Based Algorithm for Hyperspectral Image Classification (HY, YYT), pp. 1383–1388.
ICPR-2014-ZhangQWL #learning #online: Object Classification in Traffic Scene Surveillance Based on Online Semi-supervised Active Learning (ZZ, JQ, YW, ML), pp. 3086–3091.
ICPR-2014-ZhaoSJ #markov: Coupled Hidden Markov Model for Electrocorticographic Signal Classification (RZ, GS, QJ), pp. 1858–1862.
ICPR-2014-ZhuYCTJYZ #adaptation #hybrid: A Noise-Robust Adaptive Hybrid Pattern for Texture Classification (ZZ, XY, CLPC, DT, XJ, FY, JZ), pp. 1633–1638.
KDD-2014-Aggarwal #problem: The setwise stream classification problem (CCA), pp. 432–441.
KDD-2014-ChenCW #performance #scalability: Fast flux discriminant for large-scale sparse nonlinear classification (WC, YC, KQW), pp. 621–630.
KDD-2014-PrabhuV #learning #multi #named #performance: FastXML: a fast, accurate and stable tree-classifier for extreme multi-label learning (YP, MV), pp. 263–272.
KDD-2014-TsaiLL #incremental #linear: Incremental and decremental training for linear classification (CHT, CYL, CJL), pp. 343–352.
KDD-2014-VasishtDVK #learning #multi: Active learning for sparse bayesian multilabel classification (DV, ACD, MV, AK), pp. 472–481.
KDD-2014-ZhouL #mining #multi #network: Activity-edge centric multi-label classification for mining heterogeneous information networks (YZ, LL), pp. 1276–1285.
KDIR-2014-AbdallahI #modelling #n-gram #using #web: URL-based Web Page Classification — A New Method for URL-based Web Page Classification Using n-Gram Language Models (TAA, BdlI), pp. 14–21.
KDIR-2014-AlahmadiJM #concept #representation #using: Arabic Text Classification using Bag-of-Concepts Representation (AA, AJ, AEM), pp. 374–380.
KDIR-2014-AzadM #consistency #fault #heuristic: “Misclassification Error” Greedy Heuristic to Construct Decision Trees for Inconsistent Decision Tables (MA, MJM), pp. 184–191.
KDIR-2014-DomeniconiMPS #category theory: Cross-domain Text Classification through Iterative Refining of Target Categories Representations (GD, GM, RP, CS), pp. 31–42.
KDIR-2014-HafethAC #analysis #case study: Text Analysis of User-Generated Contents for Health-care Applications — Case Study on Smoking Status Classification (DAH, AA, DC), pp. 242–249.
KDIR-2014-LiuF #analysis #sentiment #topic #web: Web Content Classification based on Topic and Sentiment Analysis of Text (SL, TF), pp. 300–307.
KDIR-2014-LiuF14a #analysis #n-gram #sentiment #similarity #web: Combining N-gram based Similarity Analysis with Sentiment Analysis in Web Content Classification (SL, TF), pp. 530–537.
KDIR-2014-MohammadiMBRA #graph #parametricity: A Noise Resilient and Non-parametric Graph-based Classifier (MM, SAM, EB, BR, AA), pp. 170–175.
KDIR-2014-OliveiraBSC #automation #clustering #twitter: Combining Clustering and Classification Approaches for Reducing the Effort of Automatic Tweets Classification (EO, HGB, MRS, PMC), pp. 465–472.
KDIR-2014-SatoNS #kernel #using: A Simple Classification Method for Class Imbalanced Data using the Kernel Mean (YS, KN, AS), pp. 327–334.
KDIR-2014-TisserantRP #mining #semantics #statistics #twitter: Mining Tweet Data — Statistic and Semantic Information for Political Tweet Classification (GT, MR, VP), pp. 523–529.
KEOD-2014-TriantafyllouA: Definition and Classification of Primitives for the Robotic Unfolding of a Piece of Clothing (DT, NAA), pp. 417–422.
KMIS-2014-AngiusCMPS #semantics #social #web: Classification and Indexing of Web Content Based on a Model of Semantic Social Bookmarking (AA, GC, DM, FEP, GS), pp. 313–318.
KMIS-2014-DinsoreanuB #sentiment #twitter: Unsupervised Twitter Sentiment Classification (MD, AB), pp. 220–227.
MLDM-2014-AlbarrakCZ #image #taxonomy: Dictionary Learning-Based Volumetric Image Classification for the Diagnosis of Age-Related Macular Degeneration (AA, FC, YZ), pp. 272–284.
MLDM-2014-AlshdaifatCD #multi: A Multi-path Strategy for Hierarchical Ensemble Classification (EA, FC, KD), pp. 198–212.
MLDM-2014-AnanpiriyakulPV #multi: Label Correction Strategy on Hierarchical Multi-Label Classification (TA, PP, PV), pp. 213–227.
MLDM-2014-FuMD #multi #network #performance #towards: Towards the Efficient Recovery of General Multi-Dimensional Bayesian Network Classifier (SF, SM, MCD), pp. 16–30.
MLDM-2014-JavedA #dataset #network #social #using: Creation of Bi-lingual Social Network Dataset Using Classifiers (IJ, HA), pp. 523–533.
MLDM-2014-LarinSKKHC #parametricity #representation #using: Parametric Representation of Objects in Color Space Using One-Class Classifiers (AL, OS, AK, SYK, SCH, BHC), pp. 300–314.
MLDM-2014-MaliarskyAH: A Neuro-Genetic System for Cardiac Arrhythmia Classification (EM, MA, MH), pp. 343–360.
MLDM-2014-Manzanilla-SalazarEG #clustering #fault: Minimizing Cluster Errors in LP-Based Nonlinear Classification (OMS, JEK, UMGP), pp. 163–174.
MLDM-2014-MountassirBB #algorithm #documentation #representation: The Nearest Centroid Based on Vector Norms: A New Classification Algorithm for a New Document Representation Model (AM, HB, IB), pp. 442–456.
MLDM-2014-PirasG #generative #image #roadmap: Open Issues on Codebook Generation in Image Classification Tasks (LP, GG), pp. 328–342.
MLDM-2014-Schafer #preprocessor #towards: Towards Time Series Classification without Human Preprocessing (PS), pp. 228–242.
MLDM-2014-UtkinZC #data-driven #database #robust: A Robust One-Class Classification Model with Interval-Valued Data Based on Belief Functions and Minimax Strategy (LVU, YAZ, AIC), pp. 107–118.
MLDM-2014-WaiyamaiKSR #concept #data type #named: ACCD: Associative Classification over Concept-Drifting Data Streams (KW, TK, BS, TR), pp. 78–90.
MLDM-2014-WaiyamaiS #approach #dataset: A Cost-Sensitive Based Approach for Improving Associative Classification on Imbalanced Datasets (KW, PS), pp. 31–42.
SEKE-2014-WangKN #fault #metric #performance #predict: Choosing the Best Classification Performance Metric for Wrapper-based Software Metric Selection for Defect Prediction (HW, TMK, AN), pp. 540–545.
SIGIR-2014-BabbarPGA #approach #distributed #ranking #scalability: Re-ranking approach to classification in large-scale power-law distributed category systems (RB, IP, ÉG, MRA), pp. 1059–1062.
SIGIR-2014-BingGLNW #predict #segmentation #web: Web page segmentation with structured prediction and its application in web page classification (LB, RG, WL, ZYN, HW), pp. 767–776.
SIGIR-2014-HingmireC #approach #topic: Topic labeled text classification: a weakly supervised approach (SH, SC), pp. 385–394.
SIGIR-2014-LiWRM #interactive #named #query #retrieval: ReQ-ReC: high recall retrieval with query pooling and interactive classification (CL, YW, PR, QM), pp. 163–172.
SIGIR-2014-RenPLDR #multi #social: Hierarchical multi-label classification of social text streams (ZR, MHP, SL, WvD, MdR), pp. 213–222.
SIGIR-2014-ZhangZ0LM #overview #sentiment: Do users rate or review?: boost phrase-level sentiment labeling with review-level sentiment classification (YZ, HZ, MZ, YL, SM), pp. 1027–1030.
MoDELS-2014-GomesBA #model transformation #pattern matching #tool support: Classification of Model Transformation Tools: Pattern Matching Techniques (CG, BB, VA), pp. 619–635.
SAC-2014-BarddalGE #concept #named #network #social: SFNClassifier: a scale-free social network method to handle concept drift (JPB, HMG, FE), pp. 786–791.
SAC-2014-ChoiSP #2d #correlation #distance #image #matrix: Matrix correlation distance for 2D image classification (HC, JS, HP), pp. 1741–1742.
SAC-2014-GomesE #adaptation #data type #named #social: SAE2: advances on the social adaptive ensemble classifier for data streams (HMG, FE), pp. 798–804.
SAC-2014-OmatuY #smell #using: Smell classification using weakly responding data (SO, MY), pp. 213–214.
SAC-2014-RossiLR #algorithm #network #using: A parameter-free label propagation algorithm using bipartite heterogeneous networks for text classification (RGR, AAL, SOR), pp. 79–84.
SAC-2014-SeelandMKK: Extracting information from support vector machines for pattern-based classification (MS, AM, AK, SK), pp. 129–136.
SAC-2014-SpiegelJA #distance #performance: Fast time series classification under lucky time warping distance (SS, BJJ, SA), pp. 71–78.
SAC-2014-ZangerleS #quote #twitter: “Sorry, I was hacked”: a classification of compromised twitter accounts (EZ, GS), pp. 587–593.
SAC-2014-ZimmermannNS #adaptation: Adaptive semi supervised opinion classifier with forgetting mechanism (MZ, EN, MS), pp. 805–812.
CASE-2014-MatsumotoY #3d #framework #image: An object classification framework based on unmeasurable area patterns found in 3D range images (KM, KY), pp. 242–248.
CASE-2014-WolffNLM #lifecycle #standard: An information classification system for life cycle and manufacturing standards (SW, AN, DL, KCM), pp. 498–503.
CASE-2014-Wu: Classifications for batch service queues in production systems (KW), pp. 698–703.
DAC-2014-AlbalawiLL #algorithm #design #fixpoint #implementation #machine learning #power management: Computer-Aided Design of Machine Learning Algorithm: Training Fixed-Point Classifier for On-Chip Low-Power Implementation (HA, YL, XL), p. 6.
PDP-2014-GogolevM #network #random: Density Classification in Asynchronous Random Networks with Faulty Nodes (AG, LM), pp. 256–261.
PDP-2014-MolinaFCP #hybrid #image: Hybrid Classification of Resistors through Image Processing (RM, PF, VGC, MP), pp. 103–106.
PDP-2014-Zufferey #design #metaheuristic: Design and Classification of Ant Metaheuristics (NZ), pp. 339–343.
LICS-CSL-2014-ChenM #complexity #graph #query: One hierarchy spawns another: graph deconstructions and the complexity classification of conjunctive queries (HC, MM), p. 10.
TAP-2014-JannesariKSW #generative #parallel #testing: Generating Classified Parallel Unit Tests (AJ, NK, JS, FW), pp. 117–133.
ECSA-2013-MiesbauerW #design #overview: Classification of Design Decisions — An Expert Survey in Practice (CM, RW), pp. 130–145.
DocEng-2013-VilaresAG #twitter: Supervised polarity classification of Spanish tweets based on linguistic knowledge (DV, MAA, CGR), pp. 169–172.
DRR-2013-AriesON #algorithm #automation #clustering #summary #using: Using clustering and a modified classification algorithm for automatic text summarization (AA, HO, ON).
DRR-2013-VasilopoulosK: A classification-free word-spotting system (NV, EK).
HT-2013-CanoVRCH #social #social media #topic: Harnessing linked knowledge sources for topic classification in social media (AEC, AV, MR, FC, YH), pp. 41–50.
HT-2013-RoutBPC #approach #social: Where’s @wally?: a classification approach to geolocating users based on their social ties (DPR, KB, DPP, TC), pp. 11–20.
ICDAR-2013-AlvaroSB #hybrid #network #online: Classification of On-Line Mathematical Symbols with Hybrid Features and Recurrent Neural Networks (FA, JAS, JMB), pp. 1012–1016.
ICDAR-2013-BaechlerLI #using: Text Line Extraction Using DMLP Classifiers for Historical Manuscripts (MB, ML, RI), pp. 1029–1033.
ICDAR-2013-BougueliaBB #approach #documentation #learning: A Stream-Based Semi-supervised Active Learning Approach for Document Classification (MRB, YB, AB), pp. 611–615.
ICDAR-2013-CecottiV #multi #recognition: Rejection Schemes in Multi-class Classification — Application to Handwritten Character Recognition (HC, SV), pp. 445–449.
ICDAR-2013-ChengSAT #data fusion #image #using #visual notation: Graphical Figure Classification Using Data Fusion for Integrating Text and Image Features (BC, RJS, SA, GRT), pp. 693–697.
ICDAR-2013-GordoRKB #documentation #segmentation: Document Classification and Page Stream Segmentation for Digital Mailroom Applications (AG, MR, DK, ADB), pp. 621–625.
ICDAR-2013-HigaH #image #recognition: Local Subspace Classifier with Transformation Invariance for Appearance-Based Character Recognition in Natural Images (KH, SH), pp. 533–537.
ICDAR-2013-HoRRES #approach #documentation: Document Classification in a Non-stationary Environment: A One-Class SVM Approach (AKNH, NR, JYR, VE, NS), pp. 616–620.
ICDAR-2013-HuC #pseudo #using #verification: Offline Signature Verification Using Real Adaboost Classifier Combination of Pseudo-dynamic Features (JH, YC), pp. 1345–1349.
ICDAR-2013-ImpedovoMPBI #effectiveness #performance: Voronoi Tessellation for Effective and Efficient Handwritten Digit Classification (SI, FMM, GP, DB, DI), pp. 435–439.
ICDAR-2013-KhayyatLS #verification #word: Verification of Hierarchical Classifier Results for Handwritten Arabic Word Spotting (MK, LL, CYS), pp. 572–576.
ICDAR-2013-KimLT #heuristic #identification #using: Identification of Investigator Name Zones Using SVM Classifiers and Heuristic Rules (JK, DXL, GRT), pp. 140–144.
ICDAR-2013-KumarD #documentation #image: Unsupervised Classification of Structurally Similar Document Images (JK, DSD), pp. 1225–1229.
ICDAR-2013-LuoOWK #approach #automation #using: Automatic Chinese Text Classification Using Character-Based and Word-Based Approach (XL, WO, TW, FK), pp. 329–333.
ICDAR-2013-Siriteerakul: Mixed Thai-English Character Classification Based on Histogram of Oriented Gradient Feature (TS), pp. 847–851.
ICDAR-2013-SuTLDT #documentation #image #learning #representation: Self Learning Classification for Degraded Document Images by Sparse Representation (BS, ST, SL, TAD, CLT), pp. 155–159.
ICDAR-2013-WeiBSI #analysis #documentation #evaluation #layout: Evaluation of SVM, MLP and GMM Classifiers for Layout Analysis of Historical Documents (HW, MB, FS, RI), pp. 1220–1224.
ICDAR-2013-YanYWYYH #sorting: Sorting-Based Dynamic Classifier Ensemble Selection (YY, XCY, ZBW, XY, CY, HWH), pp. 673–677.
ICDAR-2013-YuEC #online: Mental Workload Classification via Online Writing Features (KY, JE, FC), pp. 1110–1114.
PODS-2013-ChenM #complexity #query: The fine classification of conjunctive queries and parameterized logarithmic space complexity (HC, MM), pp. 309–320.
VLDB-2013-GattaniLGTCDSRHD #approach #social #social media: Entity Extraction, Linking, Classification, and Tagging for Social Media: A Wikipedia-Based Approach (AG, DSL, NG, MT, XC, SD, SS, AR, VH, AD), pp. 1126–1137.
ICSM-2013-YukselS #analysis #automation #case study: Automated Classification of Static Code Analysis Alerts: A Case Study (UY, HS), pp. 532–535.
CHI-2013-WarrenLVG #flexibility #gesture: Bending the rules: bend gesture classification for flexible displays (KW, JL, VV, AG), pp. 607–610.
HCI-AMTE-2013-MayasHK #diagrams #process: Extending the Information of Activity Diagrams with a User Input Classification (CM, SH, HK), pp. 391–400.
HCI-III-2013-BockLSWW #automation: Audio-Based Pre-classification for Semi-automatic Facial Expression Coding (RB, KLE, IS, SW, AW), pp. 301–309.
HCI-III-2013-RukavinaGTHWTJ #automation #gender: The Impact of Gender and Sexual Hormones on Automated Psychobiological Emotion Classification (SR, SG, JWT, DH, SW, HCT, LJB), pp. 474–482.
HCI-III-2013-XuGC #kernel #representation: Kernel Based Weighted Group Sparse Representation Classifier (BX, PG, CLPC), pp. 236–245.
HCI-III-2013-YinTWDWZ #image: Classification Based on LBP and SVM for Human Embryo Microscope Images (YbY, YT, WW, FD, ZW, MZ), pp. 280–288.
HIMI-D-2013-YanagimotoSY #estimation #network #sentiment #using #word: Word Classification for Sentiment Polarity Estimation Using Neural Network (HY, MS, AY), pp. 669–677.
HIMI-LCCB-2013-TachizawaOM #automation #overview: An Automatic Classification of Product Review into Given Viewpoints (YT, MO, HM), pp. 598–606.
OCSC-2013-YuanOXS #overview #sentiment #using #web: Sentiment Classification of Web Review Using Association Rules (MY, YO, ZX, HS), pp. 442–450.
ICEIS-v1-2013-CazzolatoRYS #algorithm #data type #statistics: A Statistical Decision Tree Algorithm for Data Stream Classification (MTC, MXR, CAY, MTPS), pp. 217–223.
ICEIS-v1-2013-MoritaN #using: Classification Model using Contrast Patterns (HM, MN), pp. 334–339.
ICEIS-v1-2013-QasimR #analysis #evaluation #linear #using: Classification of Hepatitis Patients and Fibrosis Evaluation using Decision Trees and Linear Discriminant Analysis (RQ, RMR), pp. 239–246.
CIKM-2013-BagdouriWLO #towards: Towards minimizing the annotation cost of certified text classification (MB, WW, DDL, DWO), pp. 989–998.
CIKM-2013-BaoCD #topic: A partially supervised cross-collection topic model for cross-domain text classification (YB, NC, AD), pp. 239–248.
CIKM-2013-ChanYTDZW #categorisation #community #kernel #topic: Community question topic categorization via hierarchical kernelized classification (WC, WY, JT, JD, XZ, WW), pp. 959–968.
CIKM-2013-ChenW #learning #scalability: Cost-sensitive learning for large-scale hierarchical classification (JC, DW), pp. 1351–1360.
CIKM-2013-GuoZ #comprehension #empirical #graph #perspective: Understanding the roles of sub-graph features for graph classification: an empirical study perspective (TG, XZ), pp. 817–822.
CIKM-2013-HachenbergG #clustering #documentation #locality #scalability #web: Locality sensitive hashing for scalable structural classification and clustering of web documents (CH, TG), pp. 359–368.
CIKM-2013-McDowellA #network: Labels or attributes?: rethinking the neighbors for collective classification in sparsely-labeled networks (LM, DWA), pp. 847–852.
CIKM-2013-SeverynNM #ranking: Building structures from classifiers for passage reranking (AS, MN, AM), pp. 969–978.
CIKM-2013-ZhangJSCDZ #detection: Short text classification by detecting information path (SZ, XJ, DS, BC, XD, XZ), pp. 727–732.
ECIR-2013-ErmakovE #sentiment: Sentiment Classification Based on Phonetic Characteristics (SE, LE), pp. 706–709.
ECIR-2013-FuNZWJZ: Classification of Opinion Questions (HF, ZN, CZ, LW, PJ, JZ), pp. 714–717.
ECIR-2013-JeongM #dependence #recognition #using: Using WordNet Hypernyms and Dependency Features for Phrasal-Level Event Recognition and Type Classification (YJ, SHM), pp. 267–278.
ECIR-2013-JuM #incremental #ranking: Incremental Reranking for Hierarchical Text Classification (QJ, AM), pp. 726–729.
ECIR-2013-JuMJ #learning #rank: Learning to Rank from Structures in Hierarchical Text Classification (QJ, AM, RJ), pp. 183–194.
ECIR-2013-NeshatiAHB #network #social: A Joint Classification Method to Integrate Scientific and Social Networks (MN, EA, DH, HB), pp. 122–133.
ECIR-2013-NguyenTT #learning #rank #using: Folktale Classification Using Learning to Rank (DN, DT, MT), pp. 195–206.
ECIR-2013-PritsosS #automation #identification: Open-Set Classification for Automated Genre Identification (DAP, ES), pp. 207–217.
ICML-c1-2013-ChevaleyreKZ #linear: Rounding Methods for Discrete Linear Classification (YC, FK, JDZ), pp. 651–659.
ICML-c1-2013-HoJV #adaptation #crowdsourcing: Adaptive Task Assignment for Crowdsourced Classification (CJH, SJ, JWV), pp. 534–542.
ICML-c1-2013-KolarL #feature model: Feature Selection in High-Dimensional Classification (MK, HL), pp. 329–337.
ICML-c1-2013-PeleTGW #performance: The Pairwise Piecewise-Linear Embedding for Efficient Non-Linear Classification (OP, BT, AG, MW), pp. 205–213.
ICML-c1-2013-TorkamaniL: Convex Adversarial Collective Classification (MT, DL), pp. 642–650.
ICML-c1-2013-XuKWC: Cost-Sensitive Tree of Classifiers (ZEX, MJK, KQW, MC), pp. 133–141.
ICML-c2-2013-YangH #learning: Activized Learning with Uniform Classification Noise (LY, SH), pp. 370–378.
ICML-c3-2013-BaktashmotlaghHBLS #analysis #video: Non-Linear Stationary Subspace Analysis with Application to Video Classification (MB, MTH, AB, BCL, MS), pp. 450–458.
ICML-c3-2013-BiK #multi #performance: Efficient Multi-label Classification with Many Labels (WB, JTYK), pp. 405–413.
ICML-c3-2013-CortesMR #kernel #multi: Multi-Class Classification with Maximum Margin Multiple Kernel (CC, MM, AR), pp. 46–54.
ICML-c3-2013-DembczynskiJKWH #approach #multi #optimisation #plugin: Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization (KD, AJ, WK, WW, EH), pp. 1130–1138.
ICML-c3-2013-DurrantK #bound #fault: Sharp Generalization Error Bounds for Randomly-projected Classifiers (RJD, AK), pp. 693–701.
ICML-c3-2013-GermainHLM #adaptation #approach #linear: A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers (PG, AH, FL, EM), pp. 738–746.
ICML-c3-2013-Izbicki #algebra #approach #online #parallel #performance: Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training (MI), pp. 648–656.
ICML-c3-2013-LongS #consistency #multi: Consistency versus Realizable H-Consistency for Multiclass Classification (PML, RAS), pp. 801–809.
ICML-c3-2013-MenonNAC #algorithm #consistency #on the #statistics: On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance (AKM, HN, SA, SC), pp. 603–611.
ICML-c3-2013-NguyenS #algorithm #optimisation: Algorithms for Direct 0-1 Loss Optimization in Binary Classification (TN, SS), pp. 1085–1093.
ICML-c3-2013-PiresSG #bound #multi: Cost-sensitive Multiclass Classification Risk Bounds (BAP, CS, MG), pp. 1391–1399.
KDD-2013-GopalY #dependence #recursion #scalability #visual notation: Recursive regularization for large-scale classification with hierarchical and graphical dependencies (SG, YY), pp. 257–265.
KDD-2013-GuALH #graph: Selective sampling on graphs for classification (QG, CCA, JL, JH), pp. 131–139.
KDD-2013-KongCY #correlation #mining #multi #network: Multi-label classification by mining label and instance correlations from heterogeneous information networks (XK, BC, PSY), pp. 614–622.
KDD-2013-KongY #automation #distance #learning: Discriminant malware distance learning on structural information for automated malware classification (DK, GY), pp. 1357–1365.
KDD-2013-SongLLY #collaboration #microblog #process: Collaborative boosting for activity classification in microblogs (YS, ZL, CWkL, QY), pp. 482–490.
KDD-2013-ThorntonHHL #algorithm #named #optimisation: Auto-WEKA: combined selection and hyperparameter optimization of classification algorithms (CT, FH, HHH, KLB), pp. 847–855.
KDD-2013-WangS #multi #relational #social #using: Multi-label relational neighbor classification using social context features (XW, GS), pp. 464–472.
KDD-2013-YenCLLL #coordination #linear #memory management #scalability: Indexed block coordinate descent for large-scale linear classification with limited memory (IEHY, CFC, TWL, SWL, SDL), pp. 248–256.
KDIR-KMIS-2013-AlwazaePK #verification: Verifying the Usefulness of a Classification System of Best Practices (MMSA, EP, HK), pp. 405–412.
KDIR-KMIS-2013-CheetiSC #adaptation #approach #naive bayes #sentiment #syntax #using: Cross-domain Sentiment Classification using an Adapted Naïve Bayes Approach and Features Derived from Syntax Trees (SC, AS, DC), pp. 169–176.
KEOD-2013-CostaFML #approach #information management #ontology #using: Classification of Knowledge Representations using an Ontology-based Approach (RC, PF, PMNM, CL), pp. 184–191.
MLDM-2013-BijaksanaLA: A Pattern Based Two-Stage Text Classifier (MAB, YL, AA), pp. 169–182.
MLDM-2013-CastroSAE #automation #database #using #web: Automatic Classification of Web Databases Using Domain-Dictionaries (HMMC, VJSS, ILA, HJEB), pp. 340–351.
MLDM-2013-DincA #evaluation #image #random #using: Evaluation of Hyperspectral Image Classification Using Random Forest and Fukunaga-Koontz Transform (SD, RSA), pp. 234–245.
MLDM-2013-DoanDP #scalability #visual notation: Large Scale Visual Classification with Many Classes (TND, TND, FP), pp. 629–643.
MLDM-2013-EichelbergerS #empirical #multi: An Empirical Study of Reducing Multiclass Classification Methodologies (RKE, VSS), pp. 505–519.
MLDM-2013-KokkulaM #detection #synthesis #topic: Classification and Outlier Detection Based on Topic Based Pattern Synthesis (SK, NMM), pp. 99–114.
MLDM-2013-PrieditisL #bound #performance #problem #using: When Classification becomes a Problem: Using Branch-and-Bound to Improve Classification Efficiency (AP, ML), pp. 466–480.
MLDM-2013-SappP #clustering #predict: Accuracy-Based Classification EM: Combining Clustering with Prediction (SS, AP), pp. 458–465.
MLDM-2013-SigdelA #assessment #correlation #named: Pacc — A Discriminative and Accuracy Correlated Measure for Assessment of Classification Results (MS, RSA), pp. 281–295.
MLDM-2013-Suthaharan #big data #network: A Single-Domain, Representation-Learning Model for Big Data Classification of Network Intrusion (SS), pp. 296–310.
MLDM-2013-VavreckaL #feature model: EEG Feature Selection Based on Time Series Classification (MV, LL), pp. 520–527.
MLDM-2013-WilliamsHFR #distance #evaluation #probability: Area under the Distance Threshold Curve as an Evaluation Measure for Probabilistic Classifiers (SW, MH, JDF, DSR), pp. 644–657.
SEKE-2013-AlviD #fuzzy #image #using: Image Steganography Using Fuzzy Domain Transformation and Pixel Classification (AKA, RD), pp. 277–282.
SEKE-2013-KarimM #performance: Revisiting the Performance of Weighted k-Nearest Centroid Neighbor Classifiers (MRK, MM), pp. 332–337.
SIGIR-2013-BalogR #cumulative #ranking #recommendation: Cumulative citation recommendation: classification vs. ranking (KB, HR), pp. 941–944.
SIGIR-2013-HingmireCPC #documentation #topic: Document classification by topic labeling (SH, SC, GKP, SC), pp. 877–880.
SIGIR-2013-WebberBLO #effectiveness #evaluation #testing: Sequential testing in classifier evaluation yields biased estimates of effectiveness (WW, MB, DDL, DWO), pp. 933–936.
SIGIR-2013-WebberP: Assessor disagreement and text classifier accuracy (WW, JP), pp. 929–932.
SIGIR-2013-YamamotoN #music #video: Leveraging viewer comments for mood classification of music video clips (TY, SN), pp. 797–800.
POPL-2013-LivshitsC #automation #security #towards: Towards fully automatic placement of security sanitizers and declassifiers (BL, SC), pp. 385–398.
ASE-2013-NguyenT #automation #combinator #dependence #testing: Automated inference of classifications and dependencies for combinatorial testing (DCN, PT), pp. 622–627.
ICSE-2013-HerzigJZ #debugging #how #predict: It’s not a bug, it’s a feature: how misclassification impacts bug prediction (KH, SJ, AZ), pp. 392–401.
SAC-2013-AkritidisB #algorithm #machine learning #research: A supervised machine learning classification algorithm for research articles (LA, PB), pp. 115–120.
SAC-2013-BifetPRH #adaptation #data type #performance #probability: Efficient data stream classification via probabilistic adaptive windows (AB, BP, JR, GH), pp. 801–806.
SAC-2013-BlondelSU #constraints #learning #using: Learning non-linear classifiers with a sparsity constraint using L1 regularization (MB, KS, KU), pp. 167–169.
SAC-2013-PapadakisT #mutation testing #testing #using: Mutation testing strategies using mutant classification (MP, YLT), pp. 1223–1229.
DAC-2013-YuLJC #detection #feature model #using: Machine-learning-based hotspot detection using topological classification and critical feature extraction (YTY, GHL, IHRJ, CC), p. 6.
DATE-2013-BraojosAA #embedded #random #using: A methodology for embedded classification of heartbeats using random projections (RB, GA, DA), pp. 899–904.
ICST-2013-NairVSB #assessment #overview #perspective #safety: Classification, Structuring, and Assessment of Evidence for Safety — A Systematic Literature Review (SN, JLdlV, MS, LCB), pp. 94–103.
VMCAI-2013-SlabyST #database #named: ClabureDB: Classified Bug-Reports Database (JS, JS, MT), pp. 268–274.
DocEng-2012-KimHKL #library: Scientific table type classification in digital library (SK, KH, SYK, YL), pp. 133–136.
DRR-2012-ChengWAST #algorithm #image #optimisation #visual notation: Graphical image classification combining an evolutionary algorithm and binary particle swarm optimization (BC, RW, SA, RJS, GRT).
DRR-2012-KimLT #identification: Combining SVM classifiers to identify investigator name zones in biomedical articles (JK, DXL, GRT).
DRR-2012-Obafemi-AjayiAX #documentation: Ensemble methods with simple features for document zone classification (TOA, GA, BX).
DRR-2012-RamaiahKG #documentation: Handwritten document age classification based on handwriting styles (CR, GK, VG).
JCDL-2012-LeeH #generative #music #using: Generating ground truth for music mood classification using mechanical turk (JHL, XH), pp. 129–138.
PODS-2012-KostylevRS #query: Classification of annotation semirings over query containment (EVK, JLR, AZS), pp. 237–248.
TPDL-2012-SumbanaGSAV #automation #detection #wiki: Automatic Vandalism Detection in Wikipedia with Active Associative Classification (MS, MAG, RSO, JMA, AV), pp. 138–143.
ICSM-2012-PrasetyoLATL #automation #microblog: Automatic classification of software related microblogs (PKP, DL, PA, YT, EPL), pp. 596–599.
WCRE-2012-TianLS #debugging #fine-grained #information retrieval #nearest neighbour #predict: Information Retrieval Based Nearest Neighbor Classification for Fine-Grained Bug Severity Prediction (YT, DL, CS), pp. 215–224.
CIG-2012-MachadoPC #approach #automation #modelling: A binary classification approach for automatic preference modeling of virtual agents in Civilization IV (MCM, GLP, LC), pp. 155–162.
CSCW-2012-ChoudhuryDN #category theory #twitter: Unfolding the event landscape on twitter: classification and exploration of user categories (MDC, ND, MN), pp. 241–244.
ICEIS-v3-2012-HamadaASO #documentation #taxonomy #using: A Classification Method of Open-ended Questionnaires using Category-based Dictionary from Sampled Documents (KH, MA, MS, HO), pp. 193–198.
ICEIS-v3-2012-TsudaASO #automation: A Classification Method of Inquiry e-Mails for Describing FAQ with Automatic Setting Mechanism of Judgment Threshold Values (YT, MA, MS, HO), pp. 199–205.
CIKM-2012-AwadallahRW #named: PolariCQ: polarity classification of political quotations (RA, MR, GW), pp. 1945–1949.
CIKM-2012-BabbarPGA #empirical #on the #scalability #trade-off: On empirical tradeoffs in large scale hierarchical classification (RB, IP, ÉG, CA), pp. 2299–2302.
CIKM-2012-BaeK #effectiveness #recommendation: An effective category classification method based on a language model for question category recommendation on a cQA service (KB, YK), pp. 2255–2258.
CIKM-2012-ChengZXAC #learning #on the: On active learning in hierarchical classification (YC, KZ, YX, AA, ANC), pp. 2467–2470.
CIKM-2012-ChenW #automation #naive bayes: Automated feature weighting in naive bayes for high-dimensional data classification (LC, SW), pp. 1243–1252.
CIKM-2012-ChuaCBL #twitter: Community-based classification of noun phrases in twitter (FCTC, WWC, JB, EPL), pp. 1702–1706.
CIKM-2012-DuanWZS #graph #twitter: Graph-based collective classification for tweets (YD, FW, MZ, HYS), pp. 2323–2326.
CIKM-2012-EldardiryN #analysis #graph #how #predict: An analysis of how ensembles of collective classifiers improve predictions in graphs (HE, JN), pp. 225–234.
CIKM-2012-FukumotoYMS #documentation: Text classification with relatively small positive documents and unlabeled data (FF, TY, SM, YS), pp. 2315–2318.
CIKM-2012-JuLSZHL #documentation #sentiment #word: Dual word and document seed selection for semi-supervised sentiment classification (SJ, SL, YS, GZ, YH, XL), pp. 2295–2298.
CIKM-2012-KongYDW #network: Meta path-based collective classification in heterogeneous information networks (XK, PSY, YD, DJW), pp. 1567–1571.
CIKM-2012-LiangZ #performance: An efficient and simple under-sampling technique for imbalanced time series classification (GL, CZ), pp. 2339–2342.
CIKM-2012-LongCZZ #named #using: TCSST: transfer classification of short & sparse text using external data (GL, LC, XZ, CZ), pp. 764–772.
CIKM-2012-TakemuraT #twitter: Tweet classification based on their lifetime duration (HT, KT), pp. 2367–2370.
CIKM-2012-XuXLW: Coarse-to-fine sentence-level emotion classification based on the intra-sentence features and sentential context (JX, RX, QL, XW), pp. 2455–2458.
CIKM-2012-YaoS12a #web: A tag-centric discriminative model for web objects classification (LY, QZS), pp. 2247–2250.
CIKM-2012-ZerrSH #exclamation #image #privacy #retrieval: PicAlert!: a system for privacy-aware image classification and retrieval (SZ, SS, JSH), pp. 2710–2712.
CIKM-2012-ZhuCCXT #information management #mobile: Exploiting enriched contextual information for mobile app classification (HZ, HC, EC, HX, JT), pp. 1617–1621.
CIKM-2012-ZhuYCQ #approach #feature model #graph: Graph classification: a diversified discriminative feature selection approach (YZ, JXY, HC, LQ), pp. 205–214.
CIKM-2012-ZhuZYGX #parallel: Parallel proximal support vector machine for high-dimensional pattern classification (ZZ, XZ, YY, YFG, XX), pp. 2351–2354.
ECIR-2012-DasMG #identification #topic: Phrase Pair Classification for Identifying Subtopics (SD, PM, CLG), pp. 489–493.
ECIR-2012-Martinez-AlvarezYR #automation #documentation: Semi-automatic Document Classification: Exploiting Document Difficulty (MMA, SY, TR), pp. 468–471.
ECIR-2012-VitaleFS #topic: Classification of Short Texts by Deploying Topical Annotations (DV, PF, US), pp. 376–387.
ICML-2012-BelletHS #learning #linear #similarity: Similarity Learning for Provably Accurate Sparse Linear Classification (AB, AH, MS), p. 193.
ICML-2012-Ben-DavidLSS #fault #using: Minimizing The Misclassification Error Rate Using a Surrogate Convex Loss (SBD, DL, NS, KS), p. 16.
ICML-2012-Busa-FeketeBK #graph #performance #using: Fast classification using sparse decision DAGs (RBF, DB, BK), p. 99.
ICML-2012-DenchevDVN #optimisation #quantum #robust: Robust Classification with Adiabatic Quantum Optimization (VSD, ND, SVNV, HN), p. 131.
ICML-2012-GuoX #learning #multi: Cross Language Text Classification via Subspace Co-regularized Multi-view Learning (YG, MX), p. 120.
ICML-2012-JoulinB: A convex relaxation for weakly supervised classifiers (AJ, FRB), p. 171.
ICML-2012-KumarNKD #framework #kernel #learning #multi: A Binary Classification Framework for Two-Stage Multiple Kernel Learning (AK, ANM, KK, HDI), p. 173.
ICML-2012-McDowellA #hybrid: Semi-Supervised Collective Classification via Hybrid Label Regularization (LM, DWA), p. 162.
ICML-2012-MorvantKR #bound #matrix #multi: PAC-Bayesian Generalization Bound on Confusion Matrix for Multi-Class Classification (EM, SK, LR), p. 158.
ICML-2012-TakedaMK #robust: A Unified Robust Classification Model (AT, HM, TK), p. 71.
ICPR-2012-0007B #feature model #image #kernel #multi: Multiple local kernel integrated feature selection for image classification (YS, BB), pp. 2230–2233.
ICPR-2012-AliGBPNP #biology #using: Classification of biological cells using bio-inspired descriptors (WBHA, DG, MB, PP, RN, TP), pp. 3353–3357.
ICPR-2012-AroraE #automation #case study #comparative #towards: Towards automated classification of fine-art painting style: A comparative study (RSA, AME), pp. 3541–3544.
ICPR-2012-AryafarJS #automation #using: Automatic musical genre classification using sparsity-eager support vector machines (KA, SJ, AS), pp. 1526–1529.
ICPR-2012-BaiXP #image: Classification oriented semi-supervised band selection for hyperspectral images (JB, SX, CP), pp. 1888–1891.
ICPR-2012-BattiatoFGP #modelling: Aligning Bags of Shape Contexts for Blurred Shape Model based symbol classification (SB, GMF, OG, GP), pp. 1598–1601.
ICPR-2012-Berrar #comparison #null #testing #visual notation: Null QQ plots: A simple graphical alternative to significance testing for the comparison of classifiers (DPB), pp. 1852–1855.
ICPR-2012-BespalovQBS #image #scalability #using: Large-scale image classification using supervised spatial encoder (DB, YQ, BB, AS), pp. 581–584.
ICPR-2012-BougesCBL #nearest neighbour #using: Using k-nearest neighbors to handle missing weak classifiers in a boosted cascade (PB, TC, CB, GL), pp. 1763–1766.
ICPR-2012-CataldoBFM #image: Applying textural features to the classification of HEp-2 cell patterns in IIF images (SDC, AB, EF, EM), pp. 3349–3352.
ICPR-2012-ChangrampadiYG #image #multi #visual notation: Multi-class ada-boost classification of object poses through visual and infrared image information fusion (MHC, YY, IYHG), pp. 2865–2868.
ICPR-2012-ChenCZ #clique #representation: Object clique representation for scene classification (JC, XC, BZ), pp. 2829–2832.
ICPR-2012-ChenH0N #documentation: Structured document classification by matching local salient features (SC, YH, JS, SN), pp. 653–656.
ICPR-2012-ConnollyGS #correlation #on the: On the correlation between genotype and classifier diversity (JFC, EG, RS), pp. 1068–1071.
ICPR-2012-CoronaTG #multi #named #web #web service: SuStorID: A multiple classifier system for the protection of web services (IC, RT, GG), pp. 2375–2378.
ICPR-2012-CourtyAL #approach #image: A classwise supervised ordering approach for morphology based hyperspectral image classification (NC, EA, SL), pp. 1997–2000.
ICPR-2012-DongYDWYGSM #linear: A Linear Max K-min classifier (MD, LY, WD, QW, CY, JG, LS, LM), pp. 2967–2971.
ICPR-2012-DubrovinaKFSB #image #performance #robust #user interface: Efficient and robust image descriptor for GUI object classification (AD, PK, DF, SS, RB), pp. 3594–3597.
ICPR-2012-DufourZWK: Classification of drusen positions in optical coherence tomography data from patients with age-related macular degeneration (PAD, SDZ, UWS, JK), pp. 2067–2070.
ICPR-2012-ErsoyBPP #image #using: HEp-2 cell classification in IIF images using Shareboost (IE, FB, JP, KP), pp. 3362–3365.
ICPR-2012-GhoshC #analysis #automation: Feature analysis for automatic classification of HEp-2 florescence patterns : Computer-Aided Diagnosis of Auto-immune diseases (SG, VC), pp. 174–177.
ICPR-2012-GlodekSPS #markov #multi #network #using: Multi-modal Fusion based on classifiers using reject options and Markov Fusion Networks (MG, MS, GP, FS), pp. 1084–1087.
ICPR-2012-GonfausGGRG #geometry #using: Edge classification using photo-geometric features (JMG, TG, AG, FXR, JG), pp. 1497–1500.
ICPR-2012-GujraniyaM #modelling #performance #topic #using: Efficient classification using phrases generated by topic models (DG, MNM), pp. 2331–2334.
ICPR-2012-GuoRM #representation #similarity: Similarity weighted sparse representation for classification (SG, QR, ZM), pp. 1241–1244.
ICPR-2012-HanQC #adaptation #image #representation: Group sparse representation of adaptive sub-domain selection for image classification (XHH, XQ, YWC), pp. 1431–1434.
ICPR-2012-JensenED #feature model: Classification of kinematic golf putt data with emphasis on feature selection (UJ, BE, FD), pp. 1735–1738.
ICPR-2012-JoshiDGBP #analysis: Neural-net classification for spatio-temporal descriptor based depression analysis (JJ, AD, RG, MB, GP), pp. 2634–2638.
ICPR-2012-KafaiBA #clustering #estimation #network: Cluster-Classification Bayesian Networks for head pose estimation (MK, BB, LA), pp. 2869–2872.
ICPR-2012-KalkanNDL #automation: Automated classification of local patches in colon histopathology (HK, MN, RPWD, ML), pp. 61–64.
ICPR-2012-KangLXP #kernel #representation: Kernel Homotopy based sparse representation for object classification (CK, SL, SX, CP), pp. 1479–1482.
ICPR-2012-KimP #rating #visual notation: Attribute rating for classification of visual objects (JK, VP), pp. 1611–1614.
ICPR-2012-KockelkornSGRJVRSG #interactive #simulation: Interactive classification of lung tissue in CT scans by combining prior and interactively obtained training data: A simulation study (TTJPK, CIS, JCG, RR, PAdJ, MAV, JR, CSP, BvG), pp. 105–108.
ICPR-2012-KrawczykS #analysis #effectiveness #multi: Effective multiple classifier systems for breast thermogram analysis (BK, GS), pp. 3345–3348.
ICPR-2012-KrijtheHL #using: Improving cross-validation based classifier selection using meta-learning (JHK, TKH, ML), pp. 2873–2876.
ICPR-2012-KumarYD #documentation #learning #retrieval: Learning document structure for retrieval and classification (JK, PY, DSD), pp. 1558–1561.
ICPR-2012-LiDL #image #multi: Combining multi-scale dissimilarities for image classification (YL, RPWD, ML), pp. 1639–1642.
ICPR-2012-LiPMH #email #incremental #learning #using: Business email classification using incremental subspace learning (ML, YP, RM, HYH), pp. 625–628.
ICPR-2012-LiuJSET #image #segmentation: Watershed merge tree classification for electron microscopy image segmentation (TL, EJ, MS, MHE, TT), pp. 133–137.
ICPR-2012-LiuWXZS: Soft-signed sparse coding for ground-based cloud classification (SL, CW, BX, ZZ, YS), pp. 2214–2217.
ICPR-2012-LiuXFLMK #modelling #multi #statistics: Statistical modeling and signal selection in multivariate time series pattern classification (RL, SX, CF, YwL, YLM, DSK), pp. 2853–2856.
ICPR-2012-LiYLKZL #multi #using: Multiclass boosting SVM using different texture features in HEp-2 cell staining pattern classification (KL, JY, ZL, XK, RZ, WL), pp. 170–173.
ICPR-2012-Lotte: A new feature and associated optimal spatial filter for EEG signal classification: Waveform Length (FL), pp. 1302–1305.
ICPR-2012-LuLY #adaptation #kernel #learning: Adaptive kernel learning based on centered alignment for hierarchical classification (YL, JL, JY), pp. 569–572.
ICPR-2012-LuWH #gender: Gait-based gender classification in unconstrained environments (JL, GW, TSH), pp. 3284–3287.
ICPR-2012-MaoYLZ #invariant #verification: Age-invariant face verification based on Local Classifier Ensemble (XJM, YBY, NL, YZ), pp. 2408–2411.
ICPR-2012-MiyamotoMSS #3d #estimation #precise #realtime: Real-time and precise 3-D hand posture estimation based on classification tree trained with variations of appearances (SM, TM, NS, YS), pp. 453–456.
ICPR-2012-MoZW #learning: Enhancing cross-view object classification by feature-based transfer learning (YM, ZZ, YW), pp. 2218–2221.
ICPR-2012-Noh #analysis #learning #metric #nearest neighbour: χ2 Metric learning for nearest neighbor classification and its analysis (SN), pp. 991–995.
ICPR-2012-PangHYQW #analysis #learning: Theoretical analysis of learning local anchors for classification (JP, QH, BY, LQ, DW), pp. 1803–1806.
ICPR-2012-PillaiFR #multi #optimisation: F-measure optimisation in multi-label classifiers (IP, GF, FR), pp. 2424–2427.
ICPR-2012-RattaniMGR #approach #automation: A dual-staged classification-selection approach for automated update of biometric templates (AR, GLM, EG, FR), pp. 2972–2975.
ICPR-2012-RenZMZ #image #multi #optimisation: Hyperspectral image classification based on Multiple Improved particle swarm cooperative optimization and SVM (YR, YZ, QM, LZ), pp. 2274–2277.
ICPR-2012-RichterGE #image #web: Facial expression classification on web images (MR, TG, HKE), pp. 3517–3520.
ICPR-2012-RingJKE #analysis #complexity #design #embedded #performance: Software-based performance and complexity analysis for the design of embedded classification systems (MR, UJ, PK, BE), pp. 2266–2269.
ICPR-2012-RoyH #component #detection #documentation #image #using: Text detection on camera acquired document images using supervised classification of connected components in wavelet domain (UR, GH), pp. 270–273.
ICPR-2012-San-BiagioUCCCM #approach #kernel #learning #multi: A multiple kernel learning approach to multi-modal pedestrian classification (MSB, AU, MC, MC, UC, VM), pp. 2412–2415.
ICPR-2012-SantosFTRGPF #analysis #correlation #image #multi: Descriptor correlation analysis for remote sensing image multi-scale classification (JAdS, FAF, RdST, AR, PHG, SPF, AXF), pp. 3078–3081.
ICPR-2012-SantosPTGPF #image #multi #using #visual notation #word: Improving texture description in remote sensing image multi-scale classification tasks by using visual words (JAdS, OABP, RdST, PHG, SPF, AXF), pp. 3090–3093.
ICPR-2012-SchuldhausKJESL #using: Classification of surfaces and inclinations during outdoor running using shoe-mounted inertial sensors (DS, PK, UJ, BE, HS, ML), pp. 2258–2261.
ICPR-2012-SermanetCL #network: Convolutional neural networks applied to house numbers digit classification (PS, SC, YL), pp. 3288–3291.
ICPR-2012-SharmaHN #detection #incremental #learning #performance: Efficient incremental learning of boosted classifiers for object detection (PS, CH, RN), pp. 3248–3251.
ICPR-2012-SjobergKIL #concept #detection #linear #realtime #scalability #visual notation: Real-time large-scale visual concept detection with linear classifiers (MS, MK, SI, JL), pp. 421–424.
ICPR-2012-StrandmarkUK: HEp-2 staining pattern classification (PS, JU, FK), pp. 33–36.
ICPR-2012-SuYLW #bound #editing #using: Local color editing using color classification and boundary inpainting (ZS, XY, XL, DW), pp. 3196–3199.
ICPR-2012-ThakoorB #video: Structural signatures for passenger vehicle classification in video (NT, BB), pp. 926–929.
ICPR-2012-ThibaultA #performance #statistics: Efficient statistical/morphological cell texture characterization and classification (GT, JA), pp. 2440–2443.
ICPR-2012-TimofteG #collaboration #image #representation: Weighted collaborative representation and classification of images (RT, LJVG), pp. 1606–1610.
ICPR-2012-TuiaMVFR #image: Discovering relevant spatial filterbanks for VHR image classification (DT, MDM, MV, RF, AR), pp. 3212–3215.
ICPR-2012-TuS #adaptation #learning: Dynamical ensemble learning with model-friendly classifiers for domain adaptation (WT, SS), pp. 1181–1184.
ICPR-2012-TyagiKFSR #identification: Fusing biographical and biometric classifiers for improved person identification (VT, HPK, TAF, LVS, NKR), pp. 2351–2354.
ICPR-2012-Utasi #dataset: Weighted conditional mutual information based boosting for classification of imbalanced datasets (ÁU), pp. 2711–2714.
ICPR-2012-ValevY #clustering #graph #using: Classification using graph partitioning (VV, NY), pp. 1261–1264.
ICPR-2012-VieuxD #clustering #documentation #image: Hierarchical clustering model for pixel-based classification of document images (RV, JPD), pp. 290–293.
ICPR-2012-WangHWZ #gender #using: Facial image-based gender classification using Local Circular Patterns (CW, DH, YW, GZ), pp. 2432–2435.
ICPR-2012-WangWZBL #image: Adjacent coding for image classification (YW, XW, SZ, XB, WL), pp. 1459–1462.
ICPR-2012-WangXY #image #re-engineering: Sparse residue for occluded face image reconstruction and classification (JW, YX, JY), pp. 1707–1710.
ICPR-2012-WuHWT #encoding #image: Group encoding of local features in image classification (ZW, YH, LW, TT), pp. 1505–1508.
ICPR-2012-WuW #dependence: Term relevance dependency model for text classification (MSW, HMW), pp. 1064–1067.
ICPR-2012-XueCH #constraints #kernel: Discriminative indefinite kernel classifier from pairwise constraints and unlabeled data (HX, SC, JH), pp. 497–500.
ICPR-2012-XuLCYTWCTW #image #locality #performance: Efficient optic cup localization based on superpixel classification for glaucoma diagnosis in digital fundus images (YX, JL, JC, FY, NMT, DWKW, CYC, YCT, TYW), pp. 49–52.
ICPR-2012-YamasakiC #recognition #refinement: Confidence-assisted classification result refinement for object recognition featuring TopN-Exemplar-SVM (TY, TC), pp. 1783–1786.
ICPR-2012-YangGAZW #clustering #query: Iterative clustering and support vectors-based high-confidence query selection for motor imagery EEG signals classification (HY, CG, KKA, HZ, CW), pp. 2169–2172.
ICPR-2012-YanRLS #learning #multi: Active transfer learning for multi-view head-pose classification (YY, SR, OL, NS), pp. 1168–1171.
ICPR-2012-YeKC #multi: Combining general multi-class and specific two-class classifiers for improved customized ECG heartbeat classification (CY, BVKVK, MTC), pp. 2428–2431.
ICPR-2012-YiP #graph: Sparse Granger causality graphs for human action classification (SY, VP), pp. 3374–3377.
ICPR-2012-YlioinasHP #using: Age Classification in Unconstrained Conditions Using LBP Variants (JY, AH, MP), pp. 1257–1260.
ICPR-2012-ZhangHR #gender #learning: Hypergraph based semi-supervised learning for gender classification (ZZ, ERH, PR), pp. 1747–1750.
ICPR-2012-ZhangLGZ #feature model: An improved EEMD model for feature extraction and classification of gunshot in public places (ZZ, WL, WG, JZ), pp. 1517–1520.
ICPR-2012-ZhangSTW #image: Iris image classification based on color information (HZ, ZS, TT, JW), pp. 3427–3430.
ICPR-2012-ZhuoCQYX #algorithm #image #learning #using: Image classification using HTM cortical learning algorithms (WZ, ZC, YQ, ZY, YX), pp. 2452–2455.
ICPR-2012-ZnaidiaSBHP #image #multi: Bag-of-multimedia-words for image classification (AZ, AS, HLB, CH, NP), pp. 1509–1512.
KDD-2012-JanWLL: A simple methodology for soft cost-sensitive classification (TKJ, DWW, CHL, HTL), pp. 141–149.
KDD-2012-LiJPS #learning #multi: Multi-domain active learning for text classification (LL, XJ, SJP, JTS), pp. 1086–1094.
KDD-2012-LinesDHB: A shapelet transform for time series classification (JL, LMD, JH, AB), pp. 289–297.
KDD-2012-LouCG #modelling: Intelligible models for classification and regression (YL, RC, JG), pp. 150–158.
KDD-2012-YuDRZY #multi #predict: Transductive multi-label ensemble classification for protein function prediction (GXY, CD, HR, GZ, ZY), pp. 1077–1085.
KDIR-2012-HavaSK #documentation #network #semantics: Contextual Latent Semantic Networks used for Document Classification (OH, MS, PK), pp. 425–430.
KDIR-2012-LemnaruSVP #documentation #taxonomy: A System for Historical Documents Transcription based on Hierarchical Classification and Dictionary Matching (CL, ASN, MAV, RP), pp. 353–357.
KDIR-2012-LemnaruTCP #case study #detection #hybrid #network #problem: A Hybrid Solution for Imbalanced Classification Problems — Case Study on Network Intrusion Detection (CL, ATV, AC, RP), pp. 348–352.
KDIR-2012-Vanetik #dataset: Classification of Datasets with Frequent Itemsets is Wild (NV), pp. 386–389.
KEOD-2012-AlirezaieL #low level #ontology: Ontology Alignment for Classification of Low Level Sensor Data (MA, AL), pp. 89–97.
MLDM-2012-Ba-KaraitSS #hybrid #optimisation #using: EEG Signals Classification Using a Hybrid Method Based on Negative Selection and Particle Swarm Optimization (NOSBK, SMS, RS), pp. 427–438.
MLDM-2012-CarvalhoPS #image #using: Classification of Breast Tissues in Mammographic Images in Mass and Non-mass Using McIntosh’s Diversity Index and SVM (PMdSC, ACdP, ACS), pp. 482–494.
MLDM-2012-CeciAVMPG #paradigm #relational: Transductive Relational Classification in the Co-training Paradigm (MC, AA, HLV, DM, EP, HG), pp. 11–25.
MLDM-2012-DiezC #approach #multi #predict: A Multiclassifier Approach for Drill Wear Prediction (AD, AC), pp. 617–630.
MLDM-2012-ForczmanskiF #distance #representation: Classification of Elementary Stamp Shapes by Means of Reduced Point Distance Histogram Representation (PF, DF), pp. 603–616.
MLDM-2012-Garcia-ConstantinoCNRS #approach #automation #summary: A Semi-Automated Approach to Building Text Summarisation Classifiers (MGC, FC, PJN, AR, CS), pp. 495–509.
MLDM-2012-LeiteBV #algorithm #testing: Selecting Classification Algorithms with Active Testing (RL, PB, JV), pp. 117–131.
MLDM-2012-Moreira-MatiasMGB #categorisation #matrix #using: Text Categorization Using an Ensemble Classifier Based on a Mean Co-association Matrix (LMM, JMM, JG, PB), pp. 525–539.
MLDM-2012-NascimentoPS #image #using: Lung Nodules Classification in CT Images Using Shannon and Simpson Diversity Indices and SVM (LBN, ACdP, ACS), pp. 454–466.
MLDM-2012-TabatabaeiAKK #internet #machine learning: Machine Learning-Based Classification of Encrypted Internet Traffic (TST, MA, FK, MK), pp. 578–592.
MLDM-2012-Thombre #network: Comparing Logistic Regression, Neural Networks, C5.0 and M5′ Classification Techniques (AT), pp. 132–140.
MLDM-2012-YangW #modelling: Generalized Nonlinear Classification Model Based on Cross-Oriented Choquet Integral (RY, ZW), pp. 26–39.
SEKE-2012-HaoWZ #empirical #machine learning: An Empirical Study of Execution-Data Classification Based on Machine Learning (DH, XW, LZ), pp. 283–288.
SEKE-2012-NoorianBD #non-functional #product line #taxonomy: Non-functional Properties in Software Product Lines: A Taxonomy for Classification (MN, EB, WD), pp. 663–667.
SIGIR-2012-BerardiES #automation #ranking: A utility-theoretic ranking method for semi-automated text classification (GB, AE, FS), pp. 961–970.
SIGIR-2012-HuO #dataset #using: Genre classification for million song dataset using confidence-based classifiers combination (YH, MO), pp. 1083–1084.
SIGIR-2012-Ko #case study #using: A study of term weighting schemes using class information for text classification (YK), pp. 1029–1030.
SIGIR-2012-LipkaSA #clustering #information retrieval #problem: Cluster-based one-class ensemble for classification problems in information retrieval (NL, BS, MA), pp. 1041–1042.
SIGIR-2012-NishidaHF #detection #probability #twitter #word: Improving tweet stream classification by detecting changes in word probability (KN, TH, KF), pp. 971–980.
SIGIR-2012-NunzioS #data analysis #naive bayes #visual notation: A visual tool for bayesian data analysis: the impact of smoothing on naive bayes text classifiers (GMDN, AS), p. 1002.
SIGIR-2012-Sun #using #word: Short text classification using very few words (AS), pp. 1145–1146.
SIGIR-2012-ZerrSHD #image #privacy: Privacy-aware image classification and search (SZ, SS, JSH, ED), pp. 35–44.
SIGIR-2012-ZhangFQDSY #online: Emotion tagging for comments of online news by meta classification with heterogeneous information sources (YZ, YF, XQ, LD, LS, XY), pp. 1059–1060.
AdaEurope-2012-PoonCT: Choices, Choices: Comparing between CHOC’LATE and the Classification-Tree Methodology (PLP, TYC, THT), pp. 162–176.
PADL-2012-Coleman #distributed #policy #specification: Distributed Policy Specification and Interpretation with Classified Advertisements (NC), pp. 198–211.
ICSE-2012-BacchelliSDL #development #email: Content classification of development emails (AB, TDS, MD, ML), pp. 375–385.
SAC-2012-CerriBC #algorithm #multi #search-based: A genetic algorithm for Hierarchical Multi-Label Classification (RC, RCB, ACPLFdC), pp. 250–255.
SAC-2012-EgginkAB #case study: A pilot study for mood-based classification of TV programmes (JE, PA, DB), pp. 918–922.
SAC-2012-NathML #fault #on the #testing: On the improvement of a fault classification scheme with implications for white-box testing (SKN, RM, MFL), pp. 1123–1130.
SAC-2012-OongI #fuzzy #learning #multi #performance #testing: Multilayer Fuzzy ARTMAP: fast learning and fast testing for pattern classification (THO, NAMI), pp. 27–32.
SAC-2012-WickerPK #composition #matrix #multi #using: Multi-label classification using boolean matrix decomposition (JW, BP, SK), pp. 179–186.
DAC-2012-GuoYSCZ #distance #metric: Improved tangent space based distance metric for accurate lithographic hotspot classification (JG, FY, SS, CC, XZ), pp. 1173–1178.
DATE-2012-ParkKSNI: An FPGA-based accelerator for cortical object classification (MSP, SK, JS, VN, MJI), pp. 691–696.
FASE-2012-MahouachiKG #design #detection #fault: A New Design Defects Classification: Marrying Detection and Correction (RM, MK, KG), pp. 455–470.
FASE-2012-MauczkaHSSBG #automation #commit #maintenance #taxonomy #validation: Tracing Your Maintenance Work — A Cross-Project Validation of an Automated Classification Dictionary for Commit Messages (AM, MH, CS, WS, MB, TG), pp. 301–315.
CAV-2012-SharmaNA: Interpolants as Classifiers (RS, AVN, AA), pp. 71–87.
ICST-2012-KruseW #generative #sequence #testing: Test Sequence Generation from Classification Trees (PMK, JW), pp. 539–548.
ICST-2012-ShakyaXLLKK #combinator #testing #using: Isolating Failure-Inducing Combinations in Combinatorial Testing Using Test Augmentation and Classification (KS, TX, NL, YL, RK, DRK), pp. 620–623.
ICST-2012-SprenkleCP #modelling #statistics #web: Leveraging User-Privilege Classification to Customize Usage-based Statistical Models of Web Applications (SS, CC, LLP), pp. 161–170.
DRR-2011-XieA: Boosting based text and non-text region classification (BX, GA), pp. 1–10.
HT-2011-ZubiagaKS #social: Tags vs shelves: from social tagging to social classification (AZ, CK, MS), pp. 93–102.
ICDAR-2011-CiresanMGS #network: Convolutional Neural Network Committees for Handwritten Character Classification (DCC, UM, LMG, JS), pp. 1135–1139.
ICDAR-2011-DiemKS #analysis #documentation #layout: Text Classification and Document Layout Analysis of Paper Fragments (MD, FK, RS), pp. 854–858.
ICDAR-2011-ImpedovoP #multi: Updating Knowledge in Feedback-Based Multi-classifier Systems (DI, GP), pp. 227–231.
ICDAR-2011-KokawaBOWK #analysis #automation #fault: An Impact of OCR Errors on Automated Classification of OCR Japanese Texts with Parts-of-Speech Analysis (AK, LSPB, WO, TW, FK), pp. 543–547.
ICDAR-2011-KumarPD #documentation #image #learning #multi #using: Document Image Classification and Labeling Using Multiple Instance Learning (JK, JP, DSD), pp. 1059–1063.
ICDAR-2011-LuoOWK #automation #case study: A Study on Automatic Chinese Text Classification (XL, WO, TW, FK), pp. 920–924.
ICDAR-2011-NguyenCO #approach: Bags of Strokes Based Approach for Classification and Indexing of Drop Caps (TTHN, MC, JMO), pp. 349–353.
ICDAR-2011-PackerTK #recognition: alpha-Shape Based Classification with Applications to Optical Character Recognition (EP, AT, VK), pp. 344–348.
ICDAR-2011-ShivakumaraPLT #recognition #video: Video Character Recognition through Hierarchical Classification (PS, TQP, SL, CLT), pp. 131–135.
ICDAR-2011-ZhuN11a #online #recognition #scalability: A Coarse Classifier Construction Method from a Large Number of Basic Recognizers for On-line Recognition of Handwritten Japanese Characters (BZ, MN), pp. 1090–1094.
JCDL-2011-KawaseH #folksonomy #using: Classification of user interest patterns using a virtual folksonomy (RK, EH), pp. 105–108.
TPDL-2011-EckertP #library #scalability: An Application to Support Reclassification of Large Libraries (KE, MP), pp. 461–464.
VLDB-2011-KocR #incremental #maintenance #using: Incrementally maintaining classification using an RDBMS (MLK, CR), pp. 302–313.
SCAM-J-2009-HollandD11 #information management #quality #tool support: Classification and selection of tools for quality knowledge management (SH, RD), pp. 393–409.
LATA-2011-AnselmoGM #string: Classification of String Languages via Tiling Recognizable Picture Languages (MA, DG, MM), pp. 105–116.
VS-Games-2011-Anderson #game studies: A Classification of Scripting Systems for Entertainment and Serious Computer Games (EFA), pp. 47–54.
DHM-2011-TangoMAP #automation #behaviour: Automation Effects on Driver’s Behaviour When Integrating a PADAS and a Distraction Classifier (FT, LM, RA, OP), pp. 503–512.
DUXU-v2-2011-MasipOG #component #evaluation #heuristic #interactive: Classification of Interactive System Components Enables Planning Heuristic Evaluation Easier (LM, MO, TG), pp. 478–486.
HCI-MIIE-2011-KarthikP #adaptation #approach #email #machine learning: Adaptive Machine Learning Approach for Emotional Email Classification (KK, RP), pp. 552–558.
HCI-MIIE-2011-WalterSSGHSBLTS #behaviour #multimodal: Multimodal Emotion Classification in Naturalistic User Behavior (SW, SS, MS, MG, DH, MS, RB, KL, HCT, FS), pp. 603–611.
HIMI-v2-2011-MozaffariM #mining #visual notation: A Classification Scheme for Characterizing Visual Mining (EM, SPM), pp. 46–54.
ICEIS-J-2011-LemnaruP #problem: Imbalanced Classification Problems: Systematic Study, Issues and Best Practices (CL, RP), pp. 35–50.
ICEIS-v1-2011-ChagheriCRD #documentation: Document Classification — Combining Structure and Content (SC, SC, CR, CD), pp. 95–100.
ICEIS-v1-2011-PotoleaL #performance: A Comprehensive Study of the Effect of Class Imbalance on the Performance of Classifiers (RP, CL), pp. 14–21.
CIKM-2011-AnderkaSL #detection #problem #quality: Detection of text quality flaws as a one-class classification problem (MA, BS, NL), pp. 2313–2316.
CIKM-2011-BespalovBQS #analysis #n-gram #sentiment: Sentiment classification based on supervised latent n-gram analysis (DB, BB, YQ, AS), pp. 375–382.
CIKM-2011-BianC #query #taxonomy: A taxonomy of local search: semi-supervised query classification driven by information needs (JB, YC), pp. 2425–2428.
CIKM-2011-CaiZLZ #scalability #semantics #wiki: Large-scale question classification in cQA by leveraging Wikipedia semantic knowledge (LC, GZ, KL, JZ), pp. 1321–1330.
CIKM-2011-ChenSNC #adaptation #query #self: Improving context-aware query classification via adaptive self-training (MC, JTS, XN, YC), pp. 115–124.
CIKM-2011-GaoL #adaptation #analysis #probability #sentiment #using: A cross-domain adaptation method for sentiment classification using probabilistic latent analysis (SG, HL), pp. 1047–1052.
CIKM-2011-Garza #matrix: Structured data classification by means of matrix factorization (PG), pp. 2165–2168.
CIKM-2011-JacobDG #corpus #multi #social #using: Classification and annotation in social corpora using multiple relations (YJ, LD, PG), pp. 1215–1220.
CIKM-2011-LinTC #independence #sentiment #using #word: Language-independent sentiment classification using three common words (ZL, ST, XC), pp. 1041–1046.
CIKM-2011-LiuLZD #network #sentiment: Sentiment classification via l2-norm deep belief network (TL, ML, SZ, XD), pp. 2489–2492.
CIKM-2011-LiuNSC #comprehension #query #transaction: Unsupervised transactional query classification based on webpage form understanding (YL, XN, JTS, ZC), pp. 57–66.
CIKM-2011-LiZWLW #sentiment: Imbalanced sentiment classification (SL, GZ, ZW, SYML, RW), pp. 2469–2472.
CIKM-2011-LuLYYH #modelling #parametricity: Coarse-to-fine classification via parametric and nonparametric models for computer-aided diagnosis (ML, LL, XY, SY, HH), pp. 2509–2512.
CIKM-2011-QiD #evolution: Hierarchy evolution for improved classification (XQ, BDD), pp. 2193–2196.
CIKM-2011-SelvarajBSS #dataset: Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset (SKS, BB, SS, SKS), pp. 653–662.
CIKM-2011-TomasevRMI #approach #nearest neighbour #probability: A probabilistic approach to nearest-neighbor classification: naive hubness bayesian kNN (NT, MR, DM, MI), pp. 2173–2176.
CIKM-2011-VinzamuriK #convergence #design #using: Designing an ensemble classifier over subspace classifiers using iterative convergence routine (BV, KK), pp. 693–698.
CIKM-2011-WangWLZZ #analysis #approach #graph #hashtag #sentiment #topic #twitter: Topic sentiment analysis in twitter: a graph-based hashtag sentiment classification approach (XW, FW, XL, MZ, MZ), pp. 1031–1040.
CIKM-2011-WangZLBW #multi #random #using: Using random walks for multi-label classification (CW, WZ, ZL, YB, JW), pp. 2197–2200.
CIKM-2011-YooYC #email #modelling #personalisation: Modeling personalized email prioritization: classification-based and regression-based approaches (SY, YY, JGC), pp. 729–738.
ECIR-2011-Dulac-ArnoldDG #approach: Text Classification: A Sequential Reading Approach (GDA, LD, PG), pp. 411–423.
ECIR-2011-He #sentiment: Latent Sentiment Model for Weakly-Supervised Cross-Lingual Sentiment Classification (YH), pp. 214–225.
ECIR-2011-KinsellaPB #metadata #social #social media #topic #using: Topic Classification in Social Media Using Metadata from Hyperlinked Objects (SK, AP, JGB), pp. 201–206.
ECIR-2011-OhCM #modelling #scalability #taxonomy #using: Text Classification for a Large-Scale Taxonomy Using Dynamically Mixed Local and Global Models for a Node (HSO, YC, SHM), pp. 7–18.
ICML-2011-BiK #multi: MultiLabel Classification on Tree- and DAG-Structured Hierarchies (WB, JTK), pp. 17–24.
ICML-2011-CrammerG #adaptation #feedback #multi #using: Multiclass Classification with Bandit Feedback using Adaptive Regularization (KC, CG), pp. 273–280.
ICML-2011-FlachHR #performance: A Coherent Interpretation of AUC as a Measure of Aggregated Classification Performance (PAF, JHO, CFR), pp. 657–664.
ICML-2011-GabillonLGS #policy: Classification-based Policy Iteration with a Critic (VG, AL, MG, BS), pp. 1049–1056.
ICML-2011-GlorotBB #adaptation #approach #learning #scalability #sentiment: Domain Adaptation for Large-Scale Sentiment Classification: A Deep Learning Approach (XG, AB, YB), pp. 513–520.
ICML-2011-Hernandez-OralloFR #cost analysis #performance #visualisation: Brier Curves: a New Cost-Based Visualisation of Classifier Performance (JHO, PAF, CFR), pp. 585–592.
ICML-2011-KuwadekarN #learning #modelling #relational: Relational Active Learning for Joint Collective Classification Models (AK, JN), pp. 385–392.
ICML-2011-Scott #bound: Surrogate losses and regret bounds for cost-sensitive classification with example-dependent costs (CS), pp. 153–160.
ICML-2011-SuSM #multi #naive bayes #scalability #using: Large Scale Text Classification using Semisupervised Multinomial Naive Bayes (JS, JSS, SM), pp. 97–104.
ICML-2011-XiaoZW #orthogonal: Hierarchical Classification via Orthogonal Transfer (LX, DZ, MW), pp. 801–808.
KDD-2011-BekkermanG #documentation: High-precision phrase-based document classification on a modern scale (RB, MG), pp. 231–239.
KDD-2011-CerratoJG #generative: Classification of proxy labeled examples for marketing segment generation (DC, RJ, AG), pp. 343–350.
KDD-2011-IfrimW #biology #bound #coordination #predict #sequence: Bounded coordinate-descent for biological sequence classification in high dimensional predictor space (GI, CW), pp. 708–716.
KDD-2011-JiHD #network: Ranking-based classification of heterogeneous information networks (MJ, JH, MD), pp. 1298–1306.
KDD-2011-KongFY #graph: Dual active feature and sample selection for graph classification (XK, WF, PSY), pp. 654–662.
KDD-2011-MooreYZRL #learning #network: Active learning for node classification in assortative and disassortative networks (CM, XY, YZ, JBR, TL), pp. 841–849.
KDD-2011-MueenKY #named: Logical-shapelets: an expressive primitive for time series classification (AM, EJK, NEY), pp. 1154–1162.
KDD-2011-PennacchiottiP #twitter: Democrats, republicans and starbucks afficionados: user classification in twitter (MP, AMP), pp. 430–438.
KDD-2011-PereiraB #functional #using: Classification of functional magnetic resonance imaging data using informative pattern features (FP, MB), pp. 940–946.
KDD-2011-SimonKL #statistics: A simple statistical model and association rule filtering for classification (GJS, VK, PWL), pp. 823–831.
KDD-2011-WangDCV #adaptation #multi #scalability: Trading representability for scalability: adaptive multi-hyperplane machine for nonlinear classification (ZW, ND, KC, SV), pp. 24–32.
KDD-2011-WilkinsonAN #named #random: CHIRP: a new classifier based on composite hypercubes on iterated random projections (LW, AA, DTN), pp. 6–14.
KDIR-2011-AliDKB #image: Bio-inspired Bags-of-features for Image Classification (WBHA, ED, PK, MB), pp. 277–281.
KDIR-2011-ArmengolP #case study #information management #lazy evaluation #learning: Combining Two Lazy Learning Methods for Classification and Knowledge Discovery — A Case Study for Malignant Melanoma Diagnosis (EA, SP), pp. 200–207.
KDIR-2011-ClariziaCSGN11a #novel #set: A Novel Supervised Text Classifier from a Small Training Set (FC, FC, MDS, LG, PN), pp. 545–553.
KDIR-2011-CostaRO #approach #transaction #xml: A Transactional Approach to Associative XML Classification by Content and Structure (GC, RO, ER), pp. 104–113.
KDIR-2011-NguyenLT #image #multi: Cascade of Multi-level Multi-instance Classifiers for Image Annotation (CTN, HVL, TT), pp. 14–23.
KDIR-2011-PrachuabsupakijS #multi #set #using: Multi-class Data Classification for Imbalanced Data Set using Combined Sampling Approaches (WP, NS), pp. 166–171.
KDIR-2011-ShaikhSW #multi: Classification of Dialogue Acts in Urdu Multi-party Discourse (SS, TS, NW), pp. 406–412.
KEOD-2011-FukumotoS #clustering #graph #semantics #word: Semantic Classification of Unknown Words based on Graph-based Semi-supervised Clustering (FF, YS), pp. 37–46.
KEOD-2011-SuzukiF #documentation #multi #using: Multi-labeled Patent Document Classification using Technical Term Thesaurus (YS, FF), pp. 425–428.
MLDM-2011-CataltepeSBE #using: Collective Classification Using Heterogeneous Classifiers (ZÇ, AS, KB, AE), pp. 155–169.
MLDM-2011-Garcia-ConstantinoCNRST #generative #summary #using: An Investigation Concerning the Generation of Text Summarisation Classifiers Using Secondary Data (MGC, FC, PJN, AR, CS, AT), pp. 387–398.
MLDM-2011-GunesCO #algorithm #named #novel #relational #search-based #using: GA-TVRC: A Novel Relational Time Varying Classifier to Extract Temporal Information Using Genetic Algorithms (IG, ZÇ, SGÖ), pp. 568–583.
MLDM-2011-JoutsijokiJ #image: Comparing the One-vs-One and One-vs-All Methods in Benthic Macroinvertebrate Image Classification (HJ, MJ), pp. 399–413.
MLDM-2011-LiTM #hybrid #named #performance: ACE-Cost: Acquisition Cost Efficient Classifier by Hybrid Decision Tree with Local SVM Leaves (LL, UT, NDM), pp. 60–74.
MLDM-2011-LungaE #nearest neighbour: Spherical Nearest Neighbor Classification: Application to Hyperspectral Data (DL, OKE), pp. 170–184.
MLDM-2011-SanchezGM #reduction #tool support: Exploring Synergetic Effects of Dimensionality Reduction and Resampling Tools on Hyperspectral Imagery Data Classification (JSS, VG, RAM), pp. 511–523.
MLDM-2011-TomasevRMI #fuzzy #metric #nearest neighbour: Hubness-Based Fuzzy Measures for High-Dimensional k-Nearest Neighbor Classification (NT, MR, DM, MI), pp. 16–30.
MLDM-2011-YokotaY #estimation: Quadratically Constrained Maximum a Posteriori Estimation for Binary Classifier (TY, YY), pp. 1–15.
SEKE-2011-LiJ #ontology: An Ontology based Method for Building Understandable Hierarchical Classification Structure for Software Assets Browsing (GL, ZJ), pp. 521–526.
SEKE-2011-LiuZH11a #empirical #non-functional #requirements: An Empirical Study on Classification of Non-Functional Requirements (SL, RZ, XH), pp. 444–449.
SEKE-2011-NoorianBD #framework #machine learning #testing #towards: Machine Learning-based Software Testing: Towards a Classification Framework (MN, EB, WD), pp. 225–229.
SIGIR-2011-JinY #feature model #image #multi: Integrating hierarchical feature selection and classifier training for multi-label image annotation (CJ, CY), pp. 515–524.
SIGIR-2011-KimKWHK #approach #mining: Authorship classification: a discriminative syntactic tree mining approach (SK, HK, TW, JH, HDK), pp. 455–464.
SIGIR-2011-Martinez-Alvarez #information retrieval #integration #modelling: Descriptive modelling of text classification and its integration with other IR tasks (MMA), pp. 1317–1318.
SIGIR-2011-SandenZ #multi #music: Enhancing multi-label music genre classification through ensemble techniques (CS, JZZ), pp. 705–714.
SIGIR-2011-SunWY #effectiveness #towards: Towards effective short text deep classification (XS, HW, YY), pp. 1143–1144.
SIGIR-2011-WangHND #information management #matrix #using #web: Cross-language web page classification via dual knowledge transfer using nonnegative matrix tri-factorization (HW, HH, FN, CHQD), pp. 933–942.
ASE-2011-HuangNPGBT #automation #fault #generative #named #orthogonal: AutoODC: Automated generation of Orthogonal Defect Classifications (LH, VN, IP, RG, XB, JT), pp. 412–415.
ICSE-2011-Kidwell #fault #research: A decision support system for the classification of software coding faults: a research abstract (BK), pp. 1158–1160.
SAC-2011-EcharteACVL #folksonomy: A method for the classification of folksonomy resources (FE, JJA, AC, JEV, AL), pp. 1675–1680.
SAC-2011-LanLSH #algorithm #analysis #case study #comparative #image: A comparative study and analysis on K-view based algorithms for image texture classification (YL, HL, ES, CCH), pp. 859–860.
SAC-2011-LiuSGF #performance: Improving matching performance of DPI traffic classifier (TL, YS, LG, BF), pp. 514–519.
SAC-2011-OsborneGCAZ: Machine classification of melanoma and nevi from skin lesions (JDO, SG, WbC, AA, CZ), pp. 100–105.
SAC-2011-WangZG #identification #network: Traffic classification beyond application level: identifying content types from network traces (YW, ZZ, LG), pp. 540–541.
CASE-2011-NazeemR #concurrent #design #policy #resource management: Designing maximally permissive deadlock avoidance policies for sequential resource allocation systems through classification theory (AN, SAR), pp. 405–412.
DAC-2011-WangXAP #learning #policy #power management #using: Deriving a near-optimal power management policy using model-free reinforcement learning and Bayesian classification (YW, QX, ACA, MP), pp. 41–46.
DATE-2011-KangD #gpu #metaprogramming #scalability: Scalable packet classification via GPU metaprogramming (KK, YSD), pp. 871–874.
ECSA-2010-EklundA #architecture: A Classification of Value for Software Architecture Decisions (UE, TA), pp. 368–375.
DocEng-2010-SorioBDM: Open world classification of printed invoices (ES, AB, GD, EM), pp. 187–190.
DRR-2010-AwalMV #hybrid #recognition: A hybrid classifier for handwritten mathematical expression recognition (AMA, HM, CVG), pp. 1–10.
DRR-2010-KatsuyamaMHOK: A new pre-classification method based on associative matching method (YK, AM, YH, SO, NK), pp. 1–10.
DRR-2010-KimLT #naive bayes #online: Naïve Bayes and SVM classifiers for classifying databank accession number sentences from online biomedical articles (JK, DXL, GRT), pp. 1–10.
DRR-2010-YinBA #documentation #optimisation: Time and space optimization of document content classifiers (DY, HSB, CA), pp. 1–10.
ECDL-2010-AutayeuGA #lightweight #ontology #parsing: Lightweight Parsing of Classifications into Lightweight Ontologies (AA, FG, PA), pp. 327–339.
ECDL-2010-Wartena #automation #social: Automatic Classification of Social Tags (CW), pp. 176–183.
HT-2010-LexJG #online: Objectivity classification in online media (EL, AJ, MG), pp. 293–294.
JCDL-2010-HuD #library #music: Improving mood classification in music digital libraries by combining lyrics and audio (XH, JSD), pp. 159–168.
SIGMOD-2010-JinYW #graph #named #using: GAIA: graph classification using evolutionary computation (NJ, CY, WW), pp. 879–890.
ICPC-2010-Taherkhani #algorithm #sorting: Recognizing Sorting Algorithms with the C4.5 Decision Tree Classifier (AT), pp. 72–75.
LATA-2010-CabessaV #first-order #network: A Hierarchical Classification of First-Order Recurrent Neural Networks (JC, AEPV), pp. 142–153.
CHI-2010-KapoorLTH #interactive #optimisation: Interactive optimization for steering machine classification (AK, BL, DST, EH), pp. 1343–1352.
ICEIS-AIDSS-2010-KrohaN #predict #roadmap: Classification of Market News and Prediction of Market Trends (PK, RN), pp. 187–192.
ICEIS-AIDSS-2010-SahaPMB #clustering #difference #image #using: Improvement of Differential Crisp Clustering using ANN Classifier for Unsupervised Pixel Classification of Satellite Image (IS, DP, UM, SB), pp. 21–29.
ICEIS-AIDSS-2010-WatanabeRTT #statistics: Statistical Associative Classification of Mammograms — The SACMiner Method (CYVW, MXR, CTJ, AJMT), pp. 121–128.
ICEIS-J-2010-WatanabeRTT10a #image #named #statistics: SACMiner: A New Classification Method Based on Statistical Association Rules to Mine Medical Images (CYVW, MXR, CTJ, AJMT), pp. 249–263.
CIKM-2010-BatalH #predict #using: Constructing classification features using minimal predictive patterns (IB, MH), pp. 869–878.
CIKM-2010-BennettC #online: Online stratified sampling: evaluating classifiers at web-scale (PNB, VRC), pp. 1581–1584.
CIKM-2010-ChaturvediFSM #scalability: Estimating accuracy for text classification tasks on large unlabeled data (SC, TAF, LVS, MKM), pp. 889–898.
CIKM-2010-EickhoffSV #web: Web page classification on child suitability (CE, PS, APdV), pp. 1425–1428.
CIKM-2010-FiranGNP #image #order #social: Bringing order to your photos: event-driven classification of flickr images based on social knowledge (CSF, MG, WN, RP), pp. 189–198.
CIKM-2010-FujinoUN #learning #robust: A robust semi-supervised classification method for transfer learning (AF, NU, MN), pp. 379–388.
CIKM-2010-GuanXZGY #analysis #documentation #performance #reduction: Fast dimension reduction for document classification based on imprecise spectrum analysis (HG, BX, JZ, MG, TY), pp. 1753–1756.
CIKM-2010-He #learning #sentiment: Learning sentiment classification model from labeled features (YH), pp. 1685–1688.
CIKM-2010-JensenS: Exploiting sequential relationships for familial classification (LSJ, JGS), pp. 1901–1904.
CIKM-2010-LinC #multi: Mr.KNN: soft relevance for multi-label classification (XL, XwC), pp. 349–358.
CIKM-2010-LiSZJZ #documentation #named: TC-DCA: a system for text classification based on document’s content allocation (WL, LS, ZZ, XJ, WZ), pp. 1937–1938.
CIKM-2010-LiuXCY #feature model #multi: Orientation distance-based discriminative feature extraction for multi-class classification (BL, YX, LC, PSY), pp. 909–918.
CIKM-2010-Nitta #documentation #scalability #taxonomy #web: Improving taxonomies for large-scale hierarchical classifiers of web documents (KN), pp. 1649–1652.
CIKM-2010-SonPS #estimation #learning #naive bayes: Learning naïve bayes transfer classifier throughclass-wise test distribution estimation (JWS, SBP, HJS), pp. 1729–1732.
CIKM-2010-ZhuangLSHXSX #collaboration #mining #multi: Collaborative Dual-PLSA: mining distinction and commonality across multiple domains for text classification (FZ, PL, ZS, QH, YX, ZS, HX), pp. 359–368.
CIKM-2010-ZhuZGX #incremental #learning: Transfer incremental learning for pattern classification (ZZ, XZ, YFG, XX), pp. 1709–1712.
ECIR-2010-Collins-ThompsonB #performance #predict #query: Predicting Query Performance via Classification (KCT, PNB), pp. 140–152.
ICML-2010-ChengDH10a #multi: Graded Multilabel Classification: The Ordinal Case (WC, KD, EH), pp. 223–230.
ICML-2010-DembczynskiCH #multi #probability: Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains (KD, WC, EH), pp. 279–286.
ICML-2010-GoldbergE: Boosting Classifiers with Tightened L0-Relaxation Penalties (NG, JE), pp. 383–390.
ICML-2010-HariharanZVV #multi #scalability: Large Scale Max-Margin Multi-Label Classification with Priors (BH, LZM, SVNV, MV), pp. 423–430.
ICML-2010-LayB #predict #using: Supervised Aggregation of Classifiers using Artificial Prediction Markets (NL, AB), pp. 591–598.
ICML-2010-LazaricGM #algorithm #analysis #policy: Analysis of a Classification-based Policy Iteration Algorithm (AL, MG, RM), pp. 607–614.
ICML-2010-Ruping #estimation: SVM Classifier Estimation from Group Probabilities (SR), pp. 911–918.
ICML-2010-TuL #multi: One-sided Support Vector Regression for Multiclass Cost-sensitive Classification (HHT, HTL), pp. 1095–1102.
ICPR-2010-AiHRC #adaptation #component #image #independence: Adaptive Color Independent Components Based SIFT Descriptors for Image Classification (DA, XHH, XR, YWC), pp. 2436–2439.
ICPR-2010-AkbasA #image #low level #segmentation: Low-Level Image Segmentation Based Scene Classification (EA, NA), pp. 3623–3626.
ICPR-2010-AlmaksourAQC #evolution #fuzzy #gesture #incremental #learning #recognition: Evolving Fuzzy Classifiers: Application to Incremental Learning of Handwritten Gesture Recognition Systems (AA, ÉA, SQ, MC), pp. 4056–4059.
ICPR-2010-AndoF #image #segmentation: Human-Area Segmentation by Selecting Similar Silhouette Images Based on Weak-Classifier Response (HA, HF), pp. 3444–3447.
ICPR-2010-ArgunsahC #approach #human-computer #interface: AR-PCA-HMM Approach for Sensorimotor Task Classification in EEG-based Brain-Computer Interfaces (AOA, MÇ), pp. 113–116.
ICPR-2010-BayramDSM #approach: An Ensemble of Classifiers Approach to Steganalysis (SB, AED, HTS, NDM), pp. 4376–4379.
ICPR-2010-BoughorbelBB: Baby-Posture Classification from Pressure-Sensor Data (SB, FB, JB), pp. 556–559.
ICPR-2010-CanavanJRZYS #evaluation #multi: Evaluation of Multi-frame Fusion Based Face Classification Under Shadow (SJC, BJ, MR, YZ, LY, JRS), pp. 1265–1268.
ICPR-2010-CevikalpY #scalability: Large Margin Classifier Based on Affine Hulls (HC, HSY), pp. 21–24.
ICPR-2010-ChenS #nearest neighbour #scalability: Hierarchical Large Margin Nearest Neighbor Classification (QC, SS), pp. 906–909.
ICPR-2010-ChuHC #gender #identification #image #set: Identifying Gender from Unaligned Facial Images by Set Classification (WSC, CRH, CSC), pp. 2636–2639.
ICPR-2010-ConduracheMM #segmentation: An LDA-based Relative Hysteresis Classifier with Application to Segmentation of Retinal Vessels (AC, FM, AM), pp. 4202–4205.
ICPR-2010-CordellaSFMF #performance: Combining Single Class Features for Improving Performance of a Two Stage Classifier (LPC, CDS, FF, CM, ASdF), pp. 4352–4355.
ICPR-2010-DaiYW #image: Three-layer Spatial Sparse Coding for Image Classification (DD, WY, TW), pp. 613–616.
ICPR-2010-DehzangiMCL #fuzzy #using: Framewise Phone Classification Using Weighted Fuzzy Classification Rules (OD, BM, EC, HL), pp. 4186–4189.
ICPR-2010-DesnoyerW #image: Aesthetic Image Classification for Autonomous Agents (MD, DW), pp. 3452–3455.
ICPR-2010-DikmenH #canonical #correlation: Improving Classification Accuracy by Comparing Local Features through Canonical Correlations (MD, TSH), pp. 4032–4035.
ICPR-2010-DornaikaC #detection #performance #using: Efficient Object Detection and Matching Using Feature Classification (FD, FC), pp. 3073–3076.
ICPR-2010-DuGC #web: Enhancing Web Page Classification via Local Co-training (YD, XG, ZC), pp. 2905–2908.
ICPR-2010-DuinOL #multi: Classification of Volcano Events Observed by Multiple Seismic Stations (RPWD, MOA, JMLB), pp. 1052–1055.
ICPR-2010-DukkipatiYM #feature model #modelling: Maximum Entropy Model Based Classification with Feature Selection (AD, AKY, MNM), pp. 565–568.
ICPR-2010-DundarBRJSG #approach #learning #multi #towards: A Multiple Instance Learning Approach toward Optimal Classification of Pathology Slides (MD, SB, VCR, RKJ, OS, MNG), pp. 2732–2735.
ICPR-2010-DurakN #detection #image: Principal Contour Extraction and Contour Classification to Detect Coronal Loops from the Solar Images (ND, ON), pp. 2403–2406.
ICPR-2010-ErdoganS #framework #learning #linear: A Unifying Framework for Learning the Linear Combiners for Classifier Ensembles (HE, MUS), pp. 2985–2988.
ICPR-2010-ErgulA #topic #using: Scene Classification Using Spatial Pyramid of Latent Topics (EE, NA), pp. 3603–3606.
ICPR-2010-FanHM #learning #metric: Learning Metrics for Shape Classification and Discrimination (YF, DH, WM), pp. 2652–2655.
ICPR-2010-FaradjiWB #approach #problem: A Simple Approach to Find the Best Wavelet Basis in Classification Problems (FF, RKW, GEB), pp. 641–644.
ICPR-2010-FornesELV #using: Symbol Classification Using Dynamic Aligned Shape Descriptor (AF, SE, JL, EV), pp. 1957–1960.
ICPR-2010-FuLTZ #learning #music #naive bayes #retrieval: Learning Naive Bayes Classifiers for Music Classification and Retrieval (ZF, GL, KMT, DZ), pp. 4589–4592.
ICPR-2010-GargiuloS #network #performance: Improving Performance of Network Traffic Classification Systems by Cleaning Training Data (FG, CS), pp. 2768–2771.
ICPR-2010-GhanemVW #multi: Multi-class Pattern Classification in Imbalanced Data (ASG, SV, GAWW), pp. 2881–2884.
ICPR-2010-GordoP #approach #documentation #multi: A Bag-of-Pages Approach to Unordered Multi-page Document Classification (AG, FP), pp. 1920–1923.
ICPR-2010-HafnerGLUVW #image #using: Endoscopic Image Classification Using Edge-Based Features (MH, AG, ML, AU, AV, FW), pp. 2724–2727.
ICPR-2010-HanL #biology #multi: A Hierarchical GIST Model Embedding Multiple Biological Feasibilities for Scene Classification (YH, GL), pp. 3109–3112.
ICPR-2010-HeG: Rare Class Classification by Support Vector Machine (HH, AG), pp. 548–551.
ICPR-2010-Hotta #using #visual notation #word: Scene Classification Using Local Co-occurrence Feature in Subspace Obtained by KPCA of Local Blob Visual Words (KH), pp. 4230–4233.
ICPR-2010-HuangDF #estimation #multi #random: Head Pose Estimation Based on Random Forests for Multiclass Classification (CH, XD, CF), pp. 934–937.
ICPR-2010-HuangWFBHL #multimodal: Multimodal Sleeping Posture Classification (WH, AAPW, FSF, JB, CCH, KL), pp. 4336–4339.
ICPR-2010-HuWZW #gender: Combining Spatial and Temporal Information for Gait Based Gender Classification (MH, YW, ZZ, YW), pp. 3679–3682.
ICPR-2010-IdeSDTM #video: Classification of Near-Duplicate Video Segments Based on Their Appearance Patterns (II, YS, DD, TT, HM), pp. 3129–3133.
ICPR-2010-ImpedovoP #evaluation #generative #multi #set: Generating Sets of Classifiers for the Evaluation of Multi-expert Systems (DI, GP), pp. 2166–2169.
ICPR-2010-JabidKC #gender #using: Gender Classification Using Local Directional Pattern (LDP) (TJ, MHK, OC), pp. 2162–2165.
ICPR-2010-JakkojuKJ #performance #using: Fast and Spatially-Smooth Terrain Classification Using Monocular Camera (CJ, KMK, CVJ), pp. 4060–4063.
ICPR-2010-JiangWXD #image: A New Biologically Inspired Feature for Scene Image Classification (AJ, CW, BX, RD), pp. 758–761.
ICPR-2010-JunG #process: Nearest-Manifold Classification with Gaussian Processes (GJ, JG), pp. 914–917.
ICPR-2010-KhreichGMS: Boolean Combination of Classifiers in the ROC Space (WK, EG, AM, RS), pp. 4299–4303.
ICPR-2010-KimM #dataset: Dense Structure Inference for Object Classification in Aerial LIDAR Dataset (EK, GGM), pp. 3049–3052.
ICPR-2010-KobayashiO10a #image: Bag of Hierarchical Co-occurrence Features for Image Classification (TK, NO), pp. 3882–3885.
ICPR-2010-KotropoulosAP #music: Ensemble Discriminant Sparse Projections Applied to Music Genre Classification (CK, GRA, YP), pp. 822–825.
ICPR-2010-KrajewskiBK #case study #detection #multi #self #speech: Comparing Multiple Classifiers for Speech-Based Detection of Self-Confidence — A Pilot Study (JK, AB, SK), pp. 3716–3719.
ICPR-2010-KuksaP #performance #representation #sequence: Spatial Representation for Efficient Sequence Classification (PPK, VP), pp. 3320–3323.
ICPR-2010-KumarCCAPH #complexity #using: Heart Murmur Classification Using Complexity Signatures (DK, PC, RC, MA, RPP, JH), pp. 2564–2567.
ICPR-2010-LawalAM #abduction #network #recognition #using: Recognition of Handwritten Arabic (Indian) Numerals Using Freeman’s Chain Codes and Abductive Network Classifiers (IAL, REAA, SAM), pp. 1884–1887.
ICPR-2010-LeECA #case study: A Study of Voice Source and Vocal Tract Filter Based Features in Cognitive Load Classification (PNL, JE, EHCC, EA), pp. 4516–4519.
ICPR-2010-LeeWC #linear #multi: A Discriminative and Heteroscedastic Linear Feature Transformation for Multiclass Classification (HSL, HMW, BC), pp. 690–693.
ICPR-2010-LiD #multi #verification: Multi-classifier Q-stack Aging Model for Adult Face Verification (WL, AD), pp. 1310–1313.
ICPR-2010-LiGZ #representation: Local Sparse Representation Based Classification (CGL, JG, HGZ), pp. 649–652.
ICPR-2010-LiP10a #analysis #monitoring #realtime: Human State Classification and Predication for Critical Care Monitoring by Real-Time Bio-signal Analysis (XL, FP), pp. 2460–2463.
ICPR-2010-Liu10a #prototype #retrieval: One-Vs-All Training of Prototype Classifier for Pattern Classification and Retrieval (CLL), pp. 3328–3331.
ICPR-2010-LiuC #image #string: Spatial String Matching for Image Classification (YL, VC), pp. 2937–2940.
ICPR-2010-LopesGKO #music: Selection of Training Instances for Music Genre Classification (ML, FG, ALK, LESdO), pp. 4569–4572.
ICPR-2010-LotteG: Spatially Regularized Common Spatial Patterns for EEG Classification (FL, CG), pp. 3712–3715.
ICPR-2010-LuLLY #automation #image: Automated Cell Phase Classification for Zebrafish Fluorescence Microscope Images (YL, JL, TL, JY), pp. 2584–2587.
ICPR-2010-LuoN #fault #learning #multi #problem: Employing Decoding of Specific Error Correcting Codes as a New Classification Criterion in Multiclass Learning Problems (YL, KN), pp. 4238–4241.
ICPR-2010-MahdhaouiC #multi #speech: Emotional Speech Classification Based on Multi View Characterization (AM, MC), pp. 4488–4491.
ICPR-2010-MangalampalliCS #fuzzy #image #named #performance: I-FAC: Efficient Fuzzy Associative Classifier for Object Classes in Images (AM, VC, SS), pp. 4388–4391.
ICPR-2010-ManjunathMS #database #relational: A Practical Heterogeneous Classifier for Relational Databases (GM, MNM, DS), pp. 3316–3319.
ICPR-2010-Martin-HerreroF #question: Tensor-Driven Hyperspectral Denoising: A Strong Link for Classification Chains? (JMH, MFA), pp. 2820–2823.
ICPR-2010-MelendezPG #adaptation #on the #segmentation: On Adapting Pixel-based Classification to Unsupervised Texture Segmentation (JM, DP, MAG), pp. 854–857.
ICPR-2010-MozaffariBA #gender #geometry #image #using: Gender Classification Using Single Frontal Image Per Person: Combination of Appearance and Geometric Based Features (SM, HB, RA), pp. 1192–1195.
ICPR-2010-NguyenJA #automation #image #segmentation: Automated Gland Segmentation and Classification for Gleason Grading of Prostate Tissue Images (KN, AKJ, RLA), pp. 1497–1500.
ICPR-2010-NicolaouGP: Audio-Visual Classification and Fusion of Spontaneous Affective Data in Likelihood Space (MAN, HG, MP), pp. 3695–3699.
ICPR-2010-OzdemirA #image #representation #using: Image Classification Using Subgraph Histogram Representation (BÖ, SA), pp. 1112–1115.
ICPR-2010-PaclikLLD #analysis #optimisation: ROC Analysis and Cost-Sensitive Optimization for Hierarchical Classifiers (PP, CL, TL, RPWD), pp. 2977–2980.
ICPR-2010-PapaCF #dataset #optimisation: Optimizing Optimum-Path Forest Classification for Huge Datasets (JPP, FAMC, AXF), pp. 4162–4165.
ICPR-2010-Parker #empirical #feature model: An Empirical Study of Feature Extraction Methods for Audio Classification (CP), pp. 4593–4596.
ICPR-2010-PengSGS #documentation #using: Text Separation from Mixed Documents Using a Tree-Structured Classifier (XP, SS, VG, RS), pp. 241–244.
ICPR-2010-PengYZC #segmentation #using: Retinal Blood Vessels Segmentation Using the Radial Projection and Supervised Classification (QP, XY, LZ, YmC), pp. 1489–1492.
ICPR-2010-PhilippotBB #algorithm #learning #network #online: Bayesian Networks Learning Algorithms for Online Form Classification (EP, YB, AB), pp. 1981–1984.
ICPR-2010-PiroNNB: Boosting Bayesian MAP Classification (PP, RN, FN, MB), pp. 661–665.
ICPR-2010-PlumptonKLJ #linear #online #using: On-Line fMRI Data Classification Using Linear and Ensemble Classifiers (COP, LIK, DEJL, SJJ), pp. 4312–4315.
ICPR-2010-RichiardiVRB #graph #sequence: Vector Space Embedding of Undirected Graphs with Fixed-cardinality Vertex Sequences for Classification (JR, DVDV, KR, HB), pp. 902–905.
ICPR-2010-Sarkar #documentation #image #learning: Learning Image Anchor Templates for Document Classification and Data Extraction (PS), pp. 3428–3431.
ICPR-2010-Sato #design #kernel #learning: A New Learning Formulation for Kernel Classifier Design (AS), pp. 2897–2900.
ICPR-2010-SchelsS #approach #image #multi #sequence: A Multiple Classifier System Approach for Facial Expressions in Image Sequences Utilizing GMM Supervectors (MS, FS), pp. 4251–4254.
ICPR-2010-SeoAD #evaluation #performance #segmentation #tool support: Performance Evaluation Tools for Zone Segmentation and Classification (PETS) (WS, MA, DSD), pp. 503–506.
ICPR-2010-SeyedhosseiniPT #image #network #parsing: Image Parsing with a Three-State Series Neural Network Classifier (MS, ARCP, TT), pp. 4508–4511.
ICPR-2010-ShibataKI #nearest neighbour #performance #scalability: Large Margin Discriminant Hashing for Fast k-Nearest Neighbor Classification (TS, SK, SI), pp. 1015–1018.
ICPR-2010-ShivakumaraDTP #proximity #symmetry #video: A New Symmetry Based on Proximity of Wavelet-Moments for Text Frame Classification in Video (PS, AD, CLT, UP), pp. 129–132.
ICPR-2010-ShivakumaraT #novel #video: Novel Edge Features for Text Frame Classification in Video (PS, CLT), pp. 3191–3194.
ICPR-2010-ShobeirinejadG #gender #using: Gender Classification Using Interlaced Derivative Patterns (AS, YG), pp. 1509–1512.
ICPR-2010-SilvaLSBKT #documentation: Enhancing the Filtering-Out of the Back-to-Front Interference in Color Documents with a Neural Classifier (GdFPeS, RDL, JMS, SB, AK, MT), pp. 2415–2419.
ICPR-2010-Simsekli #automation #music #using: Automatic Music Genre Classification Using Bass Lines (US), pp. 4137–4140.
ICPR-2010-SternigRB #learning #multi: Inverse Multiple Instance Learning for Classifier Grids (SS, PMR, HB), pp. 770–773.
ICPR-2010-StuhlsatzLZ #feature model: Feature Extraction for Simple Classification (AS, JL, TZ), pp. 1525–1528.
ICPR-2010-SzczotFLP #adaptation: Package Boosting for Readaption of Cascaded Classifiers (MS, JF, OL, GP), pp. 552–555.
ICPR-2010-TakahashiK #approximate: Margin Preserved Approximate Convex Hulls for Classification (TT, MK), pp. 4052–4055.
ICPR-2010-Thurau #scalability: Nearest Archetype Hull Methods for Large-Scale Data Classification (CT), pp. 4040–4043.
ICPR-2010-TimmM #fault #fourier #image #statistics: Statistical Fourier Descriptors for Defect Image Classification (FT, TM), pp. 4190–4193.
ICPR-2010-TumaIP #kernel #set #using: Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets (MT, CI, MP), pp. 1011–1014.
ICPR-2010-TurkerKG #image #network #using: Classification of Polarimetric SAR Images Using Evolutionary RBF Networks (TI, SK, MG), pp. 4324–4327.
ICPR-2010-WangH10a #case study #design #multi #prototype #using: A Study of Designing Compact Recognizers of Handwritten Chinese Characters Using Multiple-Prototype Based Classifiers (YW, QH), pp. 1872–1875.
ICPR-2010-WangSLYB #using: Shape Classification Using Tree -Unions (BW, WS, WL, XY, XB), pp. 983–986.
ICPR-2010-Williams: Underwater Mine Classification with Imperfect Labels (DPW), pp. 4157–4161.
ICPR-2010-WojcikiewiczBK #clustering #image: Enhancing Image Classification with Class-wise Clustered Vocabularies (WW, AB, MK), pp. 1060–1063.
ICPR-2010-WoloszynskiK #random: A Measure of Competence Based on Randomized Reference Classifier for Dynamic Ensemble Selection (TW, MK), pp. 4194–4197.
ICPR-2010-XiaoZZS #multi: Data Classification on Multiple Manifolds (RX, QZ, DZ, PS), pp. 3898–3901.
ICPR-2010-YangC #representation: Sparse Representation Classifier Steered Discriminative Projection (JY, DC), pp. 694–697.
ICPR-2010-YinAB: Imbalance and Concentration in k-NN Classification (DY, CA, HSB), pp. 2170–2173.
ICPR-2010-YukselG #detection: Variational Mixture of Experts for Classification with Applications to Landmine Detection (SEY, PDG), pp. 2981–2984.
ICPR-2010-ZhangSW #online: A SVM-HMM Based Online Classifier for Handwritten Chemical Symbols (YZ, GS, KW), pp. 1888–1891.
ICPR-2010-ZhangWB #using: Age Classification Base on Gait Using HMM (DZ, YW, BB), pp. 3834–3837.
ICPR-2010-ZhangZYK #detection #learning #representation #taxonomy: Microaneurysm (MA) Detection via Sparse Representation Classifier with MA and Non-MA Dictionary Learning (BZ, LZ, JY, FK), pp. 277–280.
ICPR-2010-ZhangZZLL #enterprise #kernel: Gaussian ERP Kernel Classifier for Pulse Waveforms Classification (DZ, WZ, DZ, YL, NL), pp. 2736–2739.
ICPR-2010-ZhangZZZ #kernel #metric #using: Time Series Classification Using Support Vector Machine with Gaussian Elastic Metric Kernel (DZ, WZ, DZ, HZ), pp. 29–32.
ICPR-2010-ZhouCW #network #quantum: Deep Quantum Networks for Classification (SZ, QC, XW), pp. 2885–2888.
KDD-2010-AttenbergP #learning #modelling #why: Why label when you can search?: alternatives to active learning for applying human resources to build classification models under extreme class imbalance (JA, FJP), pp. 423–432.
KDD-2010-DurrantK #analysis #linear: Compressed fisher linear discriminant analysis: classification of randomly projected data (RJD, AK), pp. 1119–1128.
KDD-2010-FeiH #functional #graph: Boosting with structure information in the functional space: an application to graph classification (HF, JH), pp. 643–652.
KDD-2010-KongY #feature model #graph: Semi-supervised feature selection for graph classification (XK, PSY), pp. 793–802.
KDD-2010-Lee #learning: Learning to combine discriminative classifiers: confidence based (CHL), pp. 743–752.
KDD-2010-PrengerLVCH #bound #fault: Class-specific error bounds for ensemble classifiers (RJP, TDL, KRV, BYC, WGH), pp. 843–852.
KDD-2010-RaykarKY #design #performance #trade-off: Designing efficient cascaded classifiers: tradeoff between accuracy and cost (VCR, BK, SY), pp. 853–860.
KDD-2010-YanFDR: Medical coding classification by leveraging inter-code relationships (YY, GF, JGD, RR), pp. 193–202.
KDD-2010-YangJJZT #categorisation: Unsupervised transfer classification: application to text categorization (TY, RJ, AKJ, YZ, WT), pp. 1159–1168.
KDD-2010-YuHCL #in memory #linear #memory management #scalability: Large linear classification when data cannot fit in memory (HFY, CJH, KWC, CJL), pp. 833–842.
KDIR-2010-MuA #graph #multi: Proximity-based Graph Embeddings for Multi-label Classification (TM, SA), pp. 74–84.
KDIR-2010-Onem #behaviour #detection #network: Unwanted Behaviour Detection and Classification in Network Traffic (IMÖ), pp. 122–128.
KDIR-2010-Pavlovic-LazeticG #concept #documentation: Ontology-driven Conceptual Document Classification (GPL, JG), pp. 383–386.
KDIR-2010-Schoneberg #evaluation: Context Vector Classification — Term Classification with Context Evaluation (HS), pp. 387–391.
KDIR-2010-TsengPF #markov #using: The Typhoon Track Classification using Tri-plots and Markov Chain (JCHT, HKKP, CF), pp. 364–369.
KDIR-2010-ViswanathBK #nearest neighbour #performance #set: A Method to Generate a Reduced Training Set for Faster and Better Nearest Neighbor Classification (PV, VSB, TNK), pp. 232–236.
KEOD-2010-Alfort #approach #information retrieval: Scale and the Classificatory Dimension — A Linguistic Approach to Contextual IR (EA), pp. 370–373.
KEOD-2010-ChatterjeeKRD #automation #email #ontology #using: Automatic Email Classification using user Preference Ontology (NC, SK, SR, VD), pp. 165–170.
KEOD-2010-FukumotoS #identification: Identifying Domain-specific Senses and Its Application to Text Classification (FF, YS), pp. 263–268.
KEOD-2010-MollerSBEDS #owl #representation: Representing the International Classification of Diseases Version 10 in OWL (MM, MS, RB, PE, AD, DS), pp. 50–59.
SEKE-2010-MauczkaBG #case study #metric #process: Analyzing the Relationship of Process Metrics And Classified Changes — A Pilot Study (AM, MB, TG), pp. 269–272.
SEKE-2010-SilvaS #data mining #knowledge base #mining #modelling #relational #testing: Modeling and Testing a Knowledge Base for Instructing Users to Choose the Classification Task in Relational Data Mining (LMdS, AEAdS), pp. 608–613.
SEKE-2010-WangKG #feature model #quality: Ensemble Feature Selection Technique for Software Quality Classification (HW, TMK, KG), pp. 215–220.
SEKE-2010-XuanJRYL #automation #debugging #using: Automatic Bug Triage using Semi-Supervised Text Classification (JX, HJ, ZR, JY, ZL), pp. 209–214.
SIGIR-2010-AwadallahRW: Language-model-based pro/con classification of political text (RA, MR, GW), pp. 747–748.
SIGIR-2010-ChenYLZQ #personalisation #predict #query #question: Predicting query potential for personalization, classification or regression? (CC, MY, SL, TZ, HQ), pp. 725–726.
SIGIR-2010-CuiZC #video #web: Content-enriched classifier for web video classification (BC, CZ, GC), pp. 619–626.
SIGIR-2010-GoharianM #query #using: Context aware query classification using dynamic query window and relationship net (NG, SSRM), pp. 723–724.
SIGIR-2010-GopalY #multi: Multilabel classification with meta-level features (SG, YY), pp. 315–322.
SIGIR-2010-HongSBWJ #probability: A joint probabilistic classification model for resource selection (DH, LS, PB, MW, TJ), pp. 98–105.
SIGIR-2010-HuangAH #recommendation #tool support: Medical search and classification tools for recommendation (XH, AA, QH), p. 707.
SIGIR-2010-LiNCL #image: Entropy descriptor for image classification (HL, JN, JC, HL), pp. 753–754.
SIGIR-2010-SallesRPMMG #algorithm #documentation: Temporally-aware algorithms for document classification (TS, LCdR, GLP, FM, WMJ, MAG), pp. 307–314.
SIGIR-2010-SriramFDFD #information management #twitter: Short text classification in twitter to improve information filtering (BS, DF, ED, HF, MD), pp. 841–842.
SIGIR-2010-ZhenY #design #named: SED: supervised experimental design and its application to text classification (YZ, DYY), pp. 299–306.
SPLC-2010-TekinerdoganTS #approach #multi #product line: Multidimensional Classification Approach for Defining Product Line Engineering Transition Strategies (BT, ET, ES), pp. 461–465.
SAC-2010-BicegoLOP #array #modelling #topic #using: Expression microarray classification using topic models (MB, PL, BO, AP), pp. 1516–1520.
SAC-2010-CascaranoCR: Improving cost and accuracy of DPI traffic classifiers (NC, LC, FR), pp. 641–646.
SAC-2010-ChandaFP #documentation: Structural handwritten and machine print classification for sparse content and arbitrary oriented document fragments (SC, KF, UP), pp. 18–22.
SAC-2010-DelisVT #approach: A data perturbation approach to sensitive classification rule hiding (AD, VSV, AAT), pp. 605–609.
SAC-2010-FernandesLR #random: The impact of random samples in ensemble classifiers (PF, LL, DDAR), pp. 1002–1009.
SAC-2010-GaberS #data type #distributed #network: Distributed data stream classification for wireless sensor networks (MMG, AMS), pp. 1629–1630.
SAC-2010-GuermaziHH #analysis #image #using #web: Classification of violent web images using context based analysis (RG, MH, ABH), pp. 1768–1773.
SAC-2010-HanFD #correlation #recognition: A discriminated correlation classifier for face recognition (ZH, CF, XD), pp. 1485–1490.
SAC-2010-HeraviZ #case study #metric: A study on interestingness measures for associative classifiers (MJH, ORZ), pp. 1039–1046.
SAC-2010-LanLSH #algorithm #image #using: An improved K-view algorithm for image texture classification using new characteristic views selection methods (YL, HL, ES, CCH), pp. 959–963.
SAC-2010-MenorBBGP #markov #taxonomy #using: Virus DNA-fragment classification using taxonomic hidden Markov model profiles (MM, KB, MB, YG, GP), pp. 1567–1571.
SAC-2010-OhCM #information management: Combining global and local information for enhanced deep classification (HSO, YC, SHM), pp. 1760–1767.
SAC-2010-QinXL #nondeterminism: A Bayesian classifier for uncertain data (BQ, YX, FL), pp. 1010–1014.
SAC-2010-SillaKK #automation #hybrid #music: Improving automatic music genre classification with hybrid content-based feature vectors (CNSJ, ALK, CAAK), pp. 1702–1707.
SAC-2010-ZhangW #image #representation: Image representation and classification based on data compression (NZ, TW), pp. 981–982.
CASE-2010-ParkSR #automation #database: Image-based automated chemical database annotation with ensemble of machine-vision classifiers (JP, KS, GRR), pp. 168–173.
DAC-2010-CallegariDWA #learning #using: Classification rule learning using subgroup discovery of cross-domain attributes responsible for design-silicon mismatch (NC, DGD, LCW, MSA), pp. 374–379.
PDP-2010-Ulltveit-MoeO #privacy: Privacy Violation Classification of Snort Ruleset (NUM, VAO), pp. 654–658.
ESOP-2010-AskarovM #framework #semantics: A Semantic Framework for Declassification and Endorsement (AA, AM), pp. 64–84.
CBSE-2009-BirkmeierO #comparison #component #identification #on the #state of the art: On Component Identification Approaches — Classification, State of the Art, and Comparison (DB, SO), pp. 1–18.
WICSA-ECSA-2009-AboudAFHTUV #architecture #automation #component #concept #using: Automated architectural component classification using concept lattices (NAA, GA, JRF, MH, CT, CU, SV), pp. 21–30.
WICSA-ECSA-2009-AngelovGG #architecture #effectiveness: A classification of software reference architectures: Analyzing their success and effectiveness (SA, PWPJG, DG), pp. 141–150.
DocEng-2009-ZubiagaMF #social #web: Getting the most out of social annotations for web page classification (AZ, RM, VF), pp. 74–83.
DRR-2009-Likforman-SulemS #network #recognition: Combination of dynamic Bayesian network classifiers for the recognition of degraded characters (LLS, MS), pp. 1–10.
DRR-2009-NonnemakerB #using: Using synthetic data safely in classification (JN, HSB), pp. 1–10.
DRR-2009-Obafemi-AjayiAF #documentation #image #performance: Efficient shape-LUT classification for document image restoration (TOA, GA, OF), pp. 1–10.
ICDAR-2009-AlaeiNP: Fine Classification of Unconstrained Handwritten Persian/Arabic Numerals by Removing Confusion amongst Similar Classes (AA, PN, UP), pp. 601–605.
ICDAR-2009-AlyUFS #statistics: Statistical Classification of Spatial Relationships among Mathematical Symbols (WA, SU, AF, MS), pp. 1350–1354.
ICDAR-2009-EmmanouilidisBP #development #evaluation #locality: Development and Evaluation of Text Localization Techniques Based on Structural Texture Features and Neural Classifiers (CE, CB, NP), pp. 1270–1274.
ICDAR-2009-GordoV #documentation #invariant #layout #retrieval: A Rotation Invariant Page Layout Descriptor for Document Classification and Retrieval (AG, EV), pp. 481–485.
ICDAR-2009-HeH09a #estimation #online #using: Affine Distortion Compensation for an Isolated Online Handwritten Chinese Character Using Combined Orientation Estimation and HMM-Based Minimax Classification (TH, QH), pp. 1226–1230.
ICDAR-2009-LandreMR #difference #image #using: Ornamental Letters Image Classification Using Local Dissimilarity Maps (JL, FMN, SR), pp. 186–190.
ICDAR-2009-LinsSSFSST #documentation #image #quality: Image Classification to Improve Printing Quality of Mixed-Type Documents (RDL, GPeS, SJS, JF, MQS, PS, MT), pp. 1106–1110.
ICDAR-2009-LuqmanBR #graph #network #recognition #using: Graphic Symbol Recognition Using Graph Based Signature and Bayesian Network Classifier (MML, TB, JYR), pp. 1325–1329.
ICDAR-2009-MansjurWJ #automation #categorisation #kernel #learning #topic #using: Using Kernel Density Classifier with Topic Model and Cost Sensitive Learning for Automatic Text Categorization (DSM, TSW, BHJ), pp. 1086–1090.
ICDAR-2009-MaruyamaY #image: Extraction of Characters on Signboards in Natural Scene Images by Stump Classifiers (MM, TY), pp. 1365–1369.
ICDAR-2009-MoghaddamC #automation #clustering #documentation #image #multi #word: Application of Multi-Level Classifiers and Clustering for Automatic Word Spotting in Historical Document Images (RFM, MC), pp. 511–515.
ICDAR-2009-MoghaddamRC #approach #independence #multi #segmentation #set #using: Restoration and Segmentation of Highly Degraded Characters Using a Shape-Independent Level Set Approach and Multi-level Classifiers (RFM, DRH, MC), pp. 828–832.
ICDAR-2009-PalWK #case study #comparative #recognition #using: Comparative Study of Devnagari Handwritten Character Recognition Using Different Feature and Classifiers (UP, TW, FK), pp. 1111–1115.
ICDAR-2009-PereiraC #prototype: Prototype Selection for Handwritten Connected Digits Classification (CdSP, GDCC), pp. 1021–1025.
ICDAR-2009-PirloITS #normalisation: Combination of Measurement-Level Classifiers: Output Normalization by Dynamic Time Warping (GP, DI, CAT, ES), pp. 416–420.
ICDAR-2009-PirloTI #multi: A Feedback-Based Multi-Classifier System (GP, CAT, DI), pp. 713–717.
ICDAR-2009-RoyMSS #adaptation #framework #online #recognition: A Framework for Adaptation of the Active-DTW Classifier for Online Handwritten Character Recognition (VR, SM, AS, RRS), pp. 401–405.
ICDAR-2009-SidereHR #graph #representation: Vector Representation of Graphs: Application to the Classification of Symbols and Letters (NS, PH, JYR), pp. 681–685.
ICDAR-2009-StefanoFFM #evolution #learning #network: Learning Bayesian Networks by Evolution for Classifier Combination (CDS, FF, ASdF, AM), pp. 966–970.
ICDAR-2009-VamvakasGP #documentation #feature model #novel #recognition: A Novel Feature Extraction and Classification Methodology for the Recognition of Historical Documents (GV, BG, SJP), pp. 491–495.
ICDAR-2009-WangH #design #fault #modelling #parametricity #precise #using: Design Compact Recognizers of Handwritten Chinese Characters Using Precision Constrained Gaussian Models, Minimum Classification Error Training and Parameter Compression (YW, QH), pp. 36–40.
ICDAR-2009-Washizawa #metric: Pattern Classification on Local Metric Structure (YW), pp. 471–475.
ICDAR-2009-XuSGN #categorisation #documentation: A Hierarchical Classification Model for Document Categorization (JWX, VS, VG, DN), pp. 486–490.
ICDAR-2009-YinHTSN #multi #recognition: Rejection Strategies with Multiple Classifiers for Handwritten Character Recognition (XCY, HWH, YFT, JS, SN), pp. 1126–1130.
ICDAR-2009-ZhuSMHN #feature model: Separate Chinese Character and English Character by Cascade Classifier and Feature Selection (YZ, JS, AM, YH, SN), pp. 1191–1195.
VLDB-2009-MozafariZ #naive bayes #privacy: Publishing Naive Bayesian Classifiers: Privacy without Accuracy Loss (BM, CZ), pp. 1173–1185.
EDM-2009-HeinerZ #student: Improving Student Question Classification (CH, JLZ), pp. 259–268.
ITiCSE-2009-SkupasDR #programming: Developing classification criteria for programming tasks (BS, VD, MAR), p. 373.
ICSM-2009-FerzundAW #metric #using: Software change classification using hunk metrics (JF, SNA, FW), pp. 471–474.
TLCA-2009-TsukadaI #logic: A Logical Foundation for Environment Classifiers (TT, AI), pp. 341–355.
DiGRA-2009-DahlskogKA #functional #game studies #using: Mapping the game landscape: Locating genres using functional classification (SD, AK, EA).
CHI-2009-TalbotLKT #interactive #machine learning #multi #named #visualisation: EnsembleMatrix: interactive visualization to support machine learning with multiple classifiers (JT, BL, AK, DST), pp. 1283–1292.
DHM-2009-JeonJKH #gender #using: Facial Gender Classification Using LUT-Based Sub-images and DIE (JBJ, SHJ, DJK, KSH), pp. 36–45.
HCI-NIMT-2009-JohnsonK: Ensemble SWLDA Classifiers for the P300 Speller (GDJ, DJK), pp. 551–557.
HCI-NIMT-2009-MurakamiK #music: Study of Feature Values for Subjective Classification of Music (MM, TK), pp. 701–709.
HCI-NT-2009-LiuUC #3d #interface: Goods-Finding and Orientation in the Elderly on 3D Virtual Store Interface: The Impact of Classification and Landmarks (CLL, STU, CHC), pp. 474–483.
HIMI-DIE-2009-IshibashiN: Metadata-Based Reminder Classification in Reminiscence Engineering (MI, YN), pp. 412–418.
HIMI-DIE-2009-SrinivasSPK #feature model #performance #using: Efficient Text Classification Using Best Feature Selection and Combination of Methods (MS, KPS, EVP, SAK), pp. 437–446.
ICEIS-AIDSS-2009-TamargoGABQ: Decision Support System for Classification of Natural Risk in Maritime Construction (MAGT, ASAG, VCA, ABT, AAQ), pp. 138–143.
ICEIS-AIDSS-2009-ZhengZLL #case study #image #multi: Study on Image Classification based on SVM and the Fusion of Multiple Features (DZ, TZ, SL, YL), pp. 80–84.
ICEIS-J-2009-ChangS #analysis #performance: Fast Unsupervised Classification for Handwritten Stroke Analysis (WDC, JS), pp. 918–927.
ICEIS-J-2009-GhezziRB #delivery #mobile #platform: A Technology Classification Model for Mobile Content and Service Delivery Platforms (AG, FR, RB), pp. 600–614.
ICEIS-J-2009-GimenezHL: A Hierarchical Product-Property Model to Support Product Classification and Manage Structural and Planning Data (DMG, GPH, HPL), pp. 639–650.
ICEIS-J-2009-PapatheocharousA #fuzzy #predict: Classification and Prediction of Software Cost through Fuzzy Decision Trees (EP, ASA), pp. 234–247.
ICEIS-J-2009-SchclarR #random: Random Projection Ensemble Classifiers (AS, LR), pp. 309–316.
ICEIS-SAIC-2009-LeeLK #using: Blog Classification using K-means (KJL, ML, WK), pp. 61–67.
CIKM-2009-ArguelloCD: Classification-based resource selection (JA, JC, FD), pp. 1277–1286.
CIKM-2009-BatalH #using: Boosting KNN text classification accuracy by using supervised term weighting schemes (IB, MH), pp. 2041–2044.
CIKM-2009-CaoSXHYC #named #personalisation #query: PQC: personalized query classification (BC, JTS, EWX, DHH, QY, ZC), pp. 1217–1226.
CIKM-2009-ChenLQZ: Instance- and bag-level manifold regularization for aggregate outputs classification (SC, BL, MQ, CZ), pp. 1593–1596.
CIKM-2009-ChenTJ #detection #framework #social #social media #web: A co-classification framework for detecting web spam and spammers in social media web sites (FC, PNT, AKJ), pp. 1807–1810.
CIKM-2009-ChinavleKOF: Ensembles in adversarial classification for spam (DC, PK, TO, TF), pp. 2015–2018.
CIKM-2009-GargS #learning: Active learning in partially supervised classification (PG, SS), pp. 1783–1786.
CIKM-2009-HolzeGR #consistency #online: Consistent on-line classification of dbs workload events (MH, CG, NR), pp. 1641–1644.
CIKM-2009-JinYW #graph: Graph classification based on pattern co-occurrence (NJ, CY, WW), pp. 573–582.
CIKM-2009-KimPDG #graph #web: Improving web page classification by label-propagation over click graphs (SMK, PP, LD, SG), pp. 1077–1086.
CIKM-2009-KobayakawaKTOKT #analysis #kernel #using: Opinion classification with tree kernel SVM using linguistic modality analysis (TSK, TK, HT, NO, JDK, JT), pp. 1791–1794.
CIKM-2009-LiuZ #sentiment #using: Cross-domain sentiment classification using a two-stage method (KL, JZ), pp. 1717–1720.
CIKM-2009-MartineauFJP #difference #problem #using #word: Improving binary classification on text problems using differential word features (JM, TF, AJ, SP), pp. 2019–2024.
CIKM-2009-QiuZHZ #named #self #sentiment: SELC: a self-supervised model for sentiment classification (LQ, WZ, CH, KZ), pp. 929–936.
CIKM-2009-ShenLLZ #query: Product query classification (DS, YL, XL, DZ), pp. 741–750.
CIKM-2009-ShenWCSYCL: Exploiting term relationship to boost text classification (DS, JW, BC, JTS, QY, ZC, YL), pp. 1637–1640.
CIKM-2009-SunLL #case study #category theory #performance #predict #what: What makes categories difficult to classify?: a study on predicting classification performance for categories (AS, EPL, YL), pp. 1891–1894.
CIKM-2009-XiongLZLFZZ #information management #named #online #web: OfCourse: web content discovery, classification and information extraction for online course materials (YX, PL, YZ, FL, SF, BZ, LZ), pp. 2077–2078.
ECIR-2009-EsuliS #learning #multi: Active Learning Strategies for Multi-Label Text Classification (AE, FS), pp. 102–113.
ECIR-2009-EsuliS09a #encoding: Encoding Ordinal Features into Binary Features for Text Classification (AE, FS), pp. 771–775.
ECIR-2009-GanstererP #email: E-Mail Classification for Phishing Defense (WNG, DP), pp. 449–460.
ECIR-2009-Pablo-SanchezM #graph: Building a Graph of Names and Contextual Patterns for Named Entity Classification (CdPS, PM), pp. 530–537.
ICML-2009-Cesa-BianchiGO #bound #robust: Robust bounds for classification via selective sampling (NCB, CG, FO), pp. 121–128.
ICML-2009-DuanTXC #adaptation #multi: Domain adaptation from multiple sources via auxiliary classifiers (LD, IWT, DX, TSC), pp. 289–296.
ICML-2009-GermainLLM #learning #linear: PAC-Bayesian learning of linear classifiers (PG, AL, FL, MM), pp. 353–360.
ICML-2009-KeglB: Boosting products of base classifiers (BK, RBF), pp. 497–504.
ICML-2009-Li #adaptation #multi #named: ABC-boost: adaptive base class boost for multi-class classification (PL0), pp. 625–632.
ICML-2009-PlathTN #image #multi #random #segmentation #using: Multi-class image segmentation using conditional random fields and global classification (NP, MT, SN), pp. 817–824.
ICML-2009-UsunierBG #order #ranking: Ranking with ordered weighted pairwise classification (NU, DB, PG), pp. 1057–1064.
ICML-2009-ZhuAX #modelling #named #topic: MedLDA: maximum margin supervised topic models for regression and classification (JZ, AA, EPX), pp. 1257–1264.
KDD-2009-AmbekarWMMS #open source: Name-ethnicity classification from open sources (AA, CBW, JM, SM, SS), pp. 49–58.
KDD-2009-FormanSR #linear: Feature shaping for linear SVM classifiers (GF, MS, SR), pp. 299–308.
KDD-2009-FrankEK #approach #multi: A multi-relational approach to spatial classification (RF, ME, AJK), pp. 309–318.
KDD-2009-FuxmanKGATS #automation #using: Improving classification accuracy using automatically extracted training data (AF, AK, ABG, RA, PT, JCS), pp. 1145–1154.
KDD-2009-LoCHKS #approach #behaviour #detection #mining: Classification of software behaviors for failure detection: a discriminative pattern mining approach (DL, HC, JH, SCK, CS), pp. 557–566.
KDD-2009-LuoLXZS #case study #information management #towards #web: Towards combining web classification and web information extraction: a case study (PL, FL, YX, YZ, ZS), pp. 1235–1244.
KDD-2009-MelvilleGL #analysis #sentiment: Sentiment analysis of blogs by combining lexical knowledge with text classification (PM, WG, RDL), pp. 1275–1284.
KDD-2009-OzonatY #multi #statistics #towards #web: Towards a universal marketplace over the web: statistical multi-label classification of service provider forms with simulated annealing (KMO, DY), pp. 1295–1304.
KDD-2009-XueW #quantifier: Quantification and semi-supervised classification methods for handling changes in class distribution (JCX, GMW), pp. 897–906.
KDD-2009-YangSWC #effectiveness #learning #multi: Effective multi-label active learning for text classification (BY, JTS, TW, ZC), pp. 917–926.
KDD-2009-YinLMH #graph #social #web: Exploring social tagging graph for web object classification (ZY, RL, QM, JH), pp. 957–966.
KDIR-2009-BalujaRS #graph #performance: Text Classification through Time — Efficient Label Propagation in Time-Based Graphs (SB, DR, DS), pp. 174–182.
KDIR-2009-BruyneP: 2-class Eigen Transformation Classification Trees (SDB, FP), pp. 251–258.
KDIR-2009-ClementeDCR #behaviour #image: Behavior of Different Image Classifiers within a Broad Domain (BC, MLD, AC, PGR), pp. 278–283.
KDIR-2009-GrosserRC: Classification by Successive Neighborhood (DG, HR, NC), pp. 288–291.
KDIR-2009-VillalbaC #biology #case study #generative #reduction: Artificial Data Generation for One-class Classification — A Case Study of Dimensionality Reduction for Text and Biological Data (SDV, PC), pp. 202–210.
KEOD-2009-ReinekingSH #ontology #statistics: Evidential Combination of Ontological and Statistical Information for Active Scene Classification (TR, NS, JH), pp. 72–79.
MLDM-2009-DuangsoithongW #analysis: Relevance and Redundancy Analysis for Ensemble Classifiers (RD, TW), pp. 206–220.
MLDM-2009-GaagRFGEBF #network: Aligning Bayesian Network Classifiers with Medical Contexts (LCvdG, SR, AF, AdG, MJCE, FJB, BCJMF), pp. 787–801.
MLDM-2009-GoncalvesQ #kernel #semantics #using: Using Graph-Kernels to Represent Semantic Information in Text Classification (TG, PQ), pp. 632–646.
MLDM-2009-HasanG #adaptation #modelling: Sequential EM for Unsupervised Adaptive Gaussian Mixture Model Based Classifier (BASH, JQG), pp. 96–106.
MLDM-2009-KobayashiS #distributed #linear #representation #using: A Linear Classification Method in a Very High Dimensional Space Using Distributed Representation (TK, IS), pp. 137–147.
MLDM-2009-LiuYZZZL #scalability: A Large Margin Classifier with Additional Features (XL, JY, EZ, GZ, YZ, ML), pp. 82–95.
MLDM-2009-MoedS #performance: Efficient AdaBoost Region Classification (MM, ENS), pp. 123–136.
MLDM-2009-SilvaSNPJN #geometry #image #metric #using: Lung Nodules Classification in CT Images Using Simpson’s Index, Geometrical Measures and One-Class SVM (CAdS, ACS, SMBN, ACdP, GBJ, RAN), pp. 810–822.
MLDM-2009-StahlBA #composition #framework #induction #named #parallel: PMCRI: A Parallel Modular Classification Rule Induction Framework (FTS, MAB, MA), pp. 148–162.
MLDM-2009-WangZ #kernel: Optimal Double-Kernel Combination for Classification (FW, HZ), pp. 107–122.
MLDM-2009-ZhuFF #privacy: Preserving Privacy in Time Series Data Classification by Discretization (YZ, YF, HF), pp. 53–67.
SEKE-2009-AzizZM #requirements #towards: Towards a Classification of Requirements Relationships (RAA, DZ, TM), pp. 26–32.
SIGIR-2009-BennettN #scalability #taxonomy: Refined experts: improving classification in large taxonomies (PNB, NN), pp. 11–18.
SIGIR-2009-CaoHSJSCY #query: Context-aware query classification (HC, DHH, DS, DJ, JTS, EC, QY), pp. 3–10.
SIGIR-2009-HongD #approach: A classification-based approach to question answering in discussion boards (LH, BDD), pp. 171–178.
SIGIR-2009-LiSDZ #sentiment: Knowledge transformation for cross-domain sentiment classification (TL, VS, CHQD, YZ), pp. 716–717.
SIGIR-2009-TomasikTT #image #using: Tagging products using image classification (BT, PT, DT), pp. 792–793.
MoDELS-2009-CuccuruRGT #parametricity #uml: Constraining Type Parameters of UML 2 Templates with Substitutable Classifiers (AC, AR, SG, FT), pp. 644–649.
MoDELS-2009-CuccuruRGT #parametricity #uml: Constraining Type Parameters of UML 2 Templates with Substitutable Classifiers (AC, AR, SG, FT), pp. 644–649.
TOOLS-EUROPE-2009-KloseO #aspect-oriented #framework #monitoring #runtime: A Classification Framework for Pointcut Languages in Runtime Monitoring (KK, KO), pp. 289–307.
RE-2009-SalinesiRDM #fault #feature model #modelling #product line #towards #verification: Looking for Product Line Feature Models Defects: Towards a Systematic Classification of Verification Criteria (CS, CR, DD, RM), pp. 385–386.
SAC-2009-AraujoSSF #named #sequence #type system: HIVSetSubtype: software for subtype classification of HIV-1 sequences (LVdA, SSS, ECS, JEF), pp. 811–815.
SAC-2009-BacharM #novel #ranking: A novel distance-based classifier built on pattern ranking (DB, RM), pp. 1427–1432.
SAC-2009-BrooksI #detection #novel #visual notation: Visual detection of novel terrain via two-class classification (CAB, KI), pp. 1145–1150.
SAC-2009-FalconeFM #monitoring: Enforcement monitoring wrt. the safety-progress classification of properties (YF, JCF, LM), pp. 593–600.
SAC-2009-FangLHVAZ #image: Facial image classification of mouse embryos for the animal model study of fetal alcohol syndrome (SF, YL, JH, SVB, BA, FZ), pp. 852–856.
SAC-2009-LiuDSYH #algorithm #image #invariant #using: A new K-View algorithm for texture image classification using rotation-invariant feature (HL, SD, ES, CY, CCH), pp. 914–921.
SAC-2009-LiuTS #complexity #learning #using: Assessing complexity of service-oriented computing using learning classifier systems (LL, ST, HS), pp. 2170–2171.
SAC-2009-PlattMG #detection #topic: Improving classification based off-topic search detection via category relationships (AP, SSRM, NG), pp. 869–874.
SAC-2009-ShaLW #using #visual notation: Foreground classification using active template in the scene context for visual surveillance (XS, XL, JW), pp. 943–944.
CASE-2009-MakkapatiAA #image #segmentation: Segmentation and classification of tuberculosis bacilli from ZN-stained sputum smear images (VM, RA, RA), pp. 217–220.
CBSE-2008-ParrendF #component #java #platform #programming: Classification of Component Vulnerabilities in Java Service Oriented Programming (SOP) Platforms (PP, SF), pp. 80–96.
DRR-2008-Obafemi-AjayiAF #documentation: Ensemble LUT classification for degraded document enhancement (TOA, GA, OF), p. 681509.
DRR-2008-ReddyG: Form classification (KVUR, VG), p. 68150.
DRR-2008-ZavorinBDBS #recognition #word: Combining different classification approaches to improve off-line Arabic handwritten word recognition (IZ, EB, ED, AB, KMS), p. 681504.
ECDL-2008-PfefferES #analysis #library #visual notation: Visual Analysis of Classification Systems and Library Collections (MP, KE, HS), pp. 436–439.
SIGMOD-2008-AndoniFKPS #performance #rank #similarity: Corrigendum to “efficient similarity search and classification via rank aggregation” by Ronald Fagin, Ravi Kumar and D. Sivakumar (proc. SIGMOD’03) (AA, RF, RK, MP, DS), pp. 1375–1376.
SIGMOD-2008-PatelHL #mining: Mining relationships among interval-based events for classification (DP, WH, MLL), pp. 393–404.
VLDB-2008-LeeHLG #clustering #named #using: TraClass: trajectory classification using hierarchical region-based and trajectory-based clustering (JGL, JH, XL, HG), pp. 1081–1094.
EDM-2008-Cho #physics: Machine Classification of Peer Comments in Physics (KC), pp. 192–196.
EDM-2008-LynchAPA #graph #programming #search-based: Argument graph classification with Genetic Programming and C4.5 (CL, KDA, NP, VA), pp. 137–146.
CIG-2008-InoueS #game studies #hybrid #learning #video: Applying GA for reward allotment in an event-driven hybrid learning classifier system for soccer video games (YI, YS), pp. 296–303.
EDOC-2008-BaglioniBFST #ontology: Ontology-Based Business Plan Classification (MB, AB, BF, LS, FT), pp. 365–371.
ICEIS-AIDSS-2008-AccianiFMM #feature model #search-based #statistics: Genetic Feature Selection and Statistical Classification of Voids in Concrete Structure (GA, GF, DM, DM), pp. 231–234.
ICEIS-AIDSS-2008-StateCRP #algorithm #learning: A New Learning Algorithm for Classification in the Reduced Space (LS, CC, IR, PV), pp. 155–160.
CIKM-2008-FeiH #feature model #graph: Structure feature selection for graph classification (HF, JH), pp. 991–1000.
CIKM-2008-Forman #representation #scalability: BNS feature scaling: an improved representation over tf-idf for svm text classification (GF), pp. 263–270.
CIKM-2008-FormanK #feature model #performance: Extremely fast text feature extraction for classification and indexing (GF, EK), pp. 1221–1230.
CIKM-2008-HoefelE #learning #sequence: Learning a two-stage SVM/CRF sequence classifier (GH, CE), pp. 271–278.
CIKM-2008-RochaMPGM: Exploiting temporal contexts in text classification (LCdR, FM, AMP, MAG, WMJ), pp. 243–252.
CIKM-2008-RosenfeldFU #sequence #using #web: Using sequence classification for filtering web pages (BR, RF, LHU), pp. 1355–1356.
CIKM-2008-SongZG #framework #performance #process: A sparse gaussian processes classification framework for fast tag suggestions (YS, LZ, CLG), pp. 93–102.
CIKM-2008-ZhangJYM #effectiveness #retrieval: Improve the effectiveness of the opinion retrieval and opinion polarity classification (WZ, LJ, CTY, WM), pp. 1415–1416.
ECIR-2008-FishbeinE #encoding: Integrating Structure and Meaning: A New Method for Encoding Structure for Text Classification (JMF, CE), pp. 514–521.
ECIR-2008-FishbeinE08a #modelling #semantics: Methods for Augmenting Semantic Models with Structural Information for Text Classification (JMF, CE), pp. 575–579.
ECIR-2008-KritharaARG #documentation #fault: Semi-supervised Document Classification with a Mislabeling Error Model (AK, MRA, JMR, CG), pp. 370–381.
ECIR-2008-WiegandK #modelling #optimisation: Optimizing Language Models for Polarity Classification (MW, DK), pp. 612–616.
ICML-2008-CatanzaroSK #performance: Fast support vector machine training and classification on graphics processors (BCC, NS, KK), pp. 104–111.
ICML-2008-CevikalpTP: Nearest hyperdisk methods for high-dimensional classification (HC, BT, RP), pp. 120–127.
ICML-2008-DredzeCP #linear: Confidence-weighted linear classification (MD, KC, FP), pp. 264–271.
ICML-2008-DundarWLSR #case study #detection: Polyhedral classifier for target detection: a case study: colorectal cancer (MD, MW, SL, MS, VCR), pp. 288–295.
ICML-2008-LarochelleB #strict #using: Classification using discriminative restricted Boltzmann machines (HL, YB), pp. 536–543.
ICML-2008-LiLT #constraints #programming: Pairwise constraint propagation by semidefinite programming for semi-supervised classification (ZL, JL, XT), pp. 576–583.
ICML-2008-LongS #random: Random classification noise defeats all convex potential boosters (PML, RAS), pp. 608–615.
ICML-2008-Nijssen: Bayes optimal classification for decision trees (SN), pp. 696–703.
ICML-2008-OBrienGG #multi #probability: Cost-sensitive multi-class classification from probability estimates (DBO, MRG, RMG), pp. 712–719.
ICML-2008-PalatucciC #on the #scalability: On the chance accuracies of large collections of classifiers (MP, AC), pp. 744–751.
ICML-2008-SeldinT #category theory #clustering #multi: Multi-classification by categorical features via clustering (YS, NT), pp. 920–927.
ICML-2008-SriperumbudurLL #kernel #metric: Metric embedding for kernel classification rules (BKS, OAL, GRGL), pp. 1008–1015.
ICPR-2008-Abd-AlmageedASD #hybrid #using: Document-zone classification using partial least squares and hybrid classifiers (WAA, MA, WS, DSD), pp. 1–4.
ICPR-2008-AdankonC: Help-training for semi-supervised discriminative classifiers. Application to SVM (MMA, MC), pp. 1–4.
ICPR-2008-Bauckhage #detection #probability: Probabilistic Diffusion Classifiers for Object Detection (CB), pp. 1–4.
ICPR-2008-CaoBLLH #word: Audio-visual event classification via spatial-temporal-audio words (YC, SB, SHL, ML, SH), pp. 1–5.
ICPR-2008-ChenTZ #novel: Spam filtering with several novel bayesian classifiers (CC, YT, CZ), pp. 1–4.
ICPR-2008-ChouaibTTCV #algorithm #feature model #search-based: Feature selection combining genetic algorithm and Adaboost classifiers (HC, ORT, ST, FC, NV), pp. 1–4.
ICPR-2008-Dahyot #statistics: Bayesian classification for the Statistical Hough transform (RD), pp. 1–4.
ICPR-2008-DehzangiMCL #fuzzy #learning #speech #using: Fuzzy rule selection using Iterative Rule Learning for speech data classification (OD, BM, CES, HL), pp. 1–4.
ICPR-2008-DeselaersPN #image #modelling: Bag-of-visual-words models for adult image classification and filtering (TD, LP, HN), pp. 1–4.
ICPR-2008-EskofierHK: Classification of perceived running fatigue in digital sports (BE, FH, PK), pp. 1–4.
ICPR-2008-GamboaF #nondeterminism #testing: Uncertainty based classification fusion — a soft-biometrics test case (HG, ALNF), pp. 1–4.
ICPR-2008-GaoL #polynomial #recognition: Combining quadratic classifier and pair discriminators by pairwise coupling for handwritten Chinese character recognition (TFG, CLL), pp. 1–4.
ICPR-2008-GeorgeKK #hybrid: Hybrid wavelet support vector classification of temporal bone abnormalities (JG, STK, RK), pp. 1–4.
ICPR-2008-GhoshM #documentation #kernel #similarity #using #xml: Combining content and structure similarity for XML document classification using composite SVM kernels (SG, PM), pp. 1–4.
ICPR-2008-GuehamBC #automation #correlation #forensics #using: Automatic classification of partial shoeprints using Advanced Correlation Filters for use in forensic science (MG, AB, DC), pp. 1–4.
ICPR-2008-GuoFDH #estimation #question: Head pose estimation: Classification or regression? (GG, YF, CRD, TSH), pp. 1–4.
ICPR-2008-HadidP #gender #sequence #video: Combining motion and appearance for gender classification from video sequences (AH, MP), pp. 1–4.
ICPR-2008-Hernandez-RodriguezTC #on the #prototype: On the selection of base prototypes for LAESA and TLAESA classifiers (SHR, JFMT, JACO), pp. 1–4.
ICPR-2008-KarnickMP #approach #concept #incremental #learning #multi #using: Incremental learning in non-stationary environments with concept drift using a multiple classifier based approach (MTK, MM, RP), pp. 1–4.
ICPR-2008-KokiopoulouPF #graph #multi: Graph-based classification for multiple observations of transformed patterns (EK, SP, PF), pp. 1–4.
ICPR-2008-KottiK #database #gender #speech: Gender classification in two Emotional Speech databases (MK, CK), pp. 1–4.
ICPR-2008-LiuJ #multi: Violence classification based on shape variations from multiple views (FL, YJ), pp. 1–4.
ICPR-2008-LuFJW #framework #learning #metric #reduction #visualisation: Metric Learning: A general dimension reduction framework for classification and visualization (CL, GF, JJ, PSPW), pp. 1–4.
ICPR-2008-MunizCR #independence #using: Use of band ratioing for building illumination independent texture classification systems (RM, JAC, MRS), pp. 1–4.
ICPR-2008-PesarinCMDPT #automation #statistics: A statistical signature for automatic dialogue classification (AP, MC, VM, CD, AP, AT), pp. 1–4.
ICPR-2008-PiccardiGO #modelling #reduction: Maximum-likelihood dimensionality reduction in gaussian mixture models with an application to object classification (MP, HG, AFO), pp. 1–4.
ICPR-2008-RavesteijnVSTV: Thin layer tissue classification for electronic cleansing of CT colonography data (VFvR, FMV, IS, RT, LJvV), pp. 1–5.
ICPR-2008-RysavyFEO #random #segmentation: Classifiability criteria for refining of random walks segmentation (SR, AF, RE, KO), pp. 1–4.
ICPR-2008-Sakai #approach #incremental #monte carlo: Monte Carlo subspace method: An incremental approach to high-dimensional data classification (TS), pp. 1–4.
ICPR-2008-ScalzoBNLT #gender: Feature Fusion Hierarchies for gender classification (FS, GB, MN, LAL, AT), pp. 1–4.
ICPR-2008-SeiffertKHN #named #performance: RUSBoost: Improving classification performance when training data is skewed (CS, TMK, JVH, AN), pp. 1–4.
ICPR-2008-SerCY #hybrid #recognition #speech: A Hybrid PNN-GMM classification scheme for speech emotion recognition (WS, LC, ZLY), pp. 1–4.
ICPR-2008-SharmaCS #kernel: Bag-of-features kernel eigen spaces for classification (GS, SC, JBS), pp. 1–4.
ICPR-2008-ShidaraKN #consistency: Classification by bagged consistent itemset rules (YS, MK, AN), pp. 1–4.
ICPR-2008-SongT: C1 units for scene classification (DS, DT), pp. 1–4.
ICPR-2008-SunQ #network: Dynamic target classification in wireless sensor networks (YS, HQ), pp. 1–4.
ICPR-2008-TarghiGZ #image: Texture classification with minimal training images (ATT, JMG, AZ), pp. 1–4.
ICPR-2008-TeynorB: Wavelet-based salient points with scale information for classification (AT, HB), pp. 1–5.
ICPR-2008-TominagaY: Metal-dielectric object classification by polarization degree map (ST, TY), pp. 1–4.
ICPR-2008-UchidaA #recognition: Early recognition of sequential patterns by classifier combination (SU, KA), pp. 1–4.
ICPR-2008-VillS #analysis #automation: Automated stroke ending analysis for drawing tool classification (MCV, RS), pp. 1–4.
ICPR-2008-WangC #semantics #using: Film shot classification using directing semantics (HLW, LFC), pp. 1–4.
ICPR-2008-WangI #image #markov #modelling #multi #semantics: Combining multiple spatial hidden Markov models in image semantic classification and annotation (LW, HHSI), pp. 1–4.
ICPR-2008-WimmerHS #bound: Implicit active shape model employing boundary classifier (AW, JH, GS), pp. 1–4.
ICPR-2008-WuF #3d #learning #multi #using: Multiple view based 3D object classification using ensemble learning of local subspaces (JW, KF), pp. 1–4.
ICPR-2008-WuSH #gender: Gender classification based on facial surface normals (JW, WAPS, ERH), pp. 1–4.
ICPR-2008-YamaguchiM #categorisation #image #probability #topic: Image categorization by a classifier based on probabilistic topic model (TY, MM), pp. 1–4.
ICPR-2008-YarlagaddaOM #3d #distance: Lie group distance based generic 3-d vehicle classification (PY, ÖCÖ, JLM), pp. 1–4.
ICPR-2008-YuS #visual notation: FastWavelet-Based Visual Classification (GY, JJES), pp. 1–5.
ICPR-2008-YuW #3d #clustering #knowledge base: Knowledge based cluster ensemble for 3D head model classification (ZY, HSW), pp. 1–4.
ICPR-2008-ZhangLHT #automation: Boosting local feature descriptors for automatic objects classification in traffic scene surveillance (ZZ, ML, KH, TT), pp. 1–4.
ICPR-2008-ZhongGA #algorithm: Properties of the k-norm pruning algorithm for decision tree classifiers (MZ, MG, GCA), pp. 1–4.
ICPR-2008-ZhouWS #process #recognition #using: Human motion recognition using Gaussian Processes classification (HZ, LW, DS), pp. 1–4.
KDD-2008-BilgicG #effectiveness: Effective label acquisition for collective classification (MB, LG), pp. 43–51.
KDD-2008-ChenJCLWY #kernel #learning: Learning subspace kernels for classification (JC, SJ, BC, QL, MW, JY), pp. 106–114.
KDD-2008-ChenW #feature model #metric #named #performance #problem: FAST: a roc-based feature selection metric for small samples and imbalanced data classification problems (XwC, MW), pp. 124–132.
KDD-2008-Christen #automation #nearest neighbour #using: Automatic record linkage using seeded nearest neighbour and support vector machine classification (PC), pp. 151–159.
KDD-2008-ElkanN #learning: Learning classifiers from only positive and unlabeled data (CE, KN), pp. 213–220.
KDD-2008-FormanR #file system #scalability: Scaling up text classification for large file systems (GF, SR), pp. 239–246.
KDD-2008-GallagherTEF #network #using: Using ghost edges for classification in sparsely labeled networks (BG, HT, TER, CF), pp. 256–264.
KDD-2008-GodboleR #analysis #automation #industrial: Text classification, business intelligence, and interactivity: automating C-Sat analysis for services industry (SG, SR), pp. 911–919.
KDD-2008-JiTYY #multi: Extracting shared subspace for multi-label classification (SJ, LT, SY, JY), pp. 381–389.
KDD-2008-NguyenC: Classification with partial labels (NN, RC), pp. 551–559.
KDD-2008-SunJY #learning #multi: Hypergraph spectral learning for multi-label classification (LS, SJ, JY), pp. 668–676.
KDD-2008-WangD #kernel #semantics #using #wiki: Building semantic kernels for text classification using wikipedia (PW, CD), pp. 713–721.
SEKE-2008-Chao #data type #privacy: Privacy-preserving Classification of Data Streams (CMC), pp. 603–606.
SEKE-2008-FollecoKB #quality: Analyzing the Impact of Attribute Noise on Software Quality Classification (AF, TMK, LAB), pp. 73–78.
SEKE-2008-LucasSM #personalisation #recommendation #towards #using: Comparing the Use of Traditional and Associative Classifiers towards Personalized Recommendations (JPL, SS, MNMG), pp. 607–612.
SIGIR-2008-Banerjee #corpus #modelling #topic #using: Improving text classification accuracy using topic modeling over an additional corpus (SB), pp. 867–868.
SIGIR-2008-CrainHZ #scalability: A scalable assistant librarian: hierarchical subject classification of books (SPC, JH, HZ), pp. 799–800.
SIGIR-2008-ElgersmaR: Personal vs non-personal blogs: initial classification experiments (EE, MdR), pp. 723–724.
SIGIR-2008-PanTLL #kernel #semantics: Question classification with semantic tree kernel (YP, YT, LL, YL), pp. 837–838.
SIGIR-2008-QiD #web: Classifiers without borders: incorporating fielded text from neighboring web pages (XQ, BDD), pp. 643–650.
SIGIR-2008-WestDHJ #music #visualisation: Dynamic visualization of music classification systems (KW, JSD, XH, MCJ), p. 888.
SIGIR-2008-WuO #topic: Bilingual topic aspect classification with a few training examples (YW, DWO), pp. 203–210.
SIGIR-2008-XueDYY #topic: Topic-bridged PLSA for cross-domain text classification (GRX, WD, QY, YY), pp. 627–634.
SIGIR-2008-XueXYY #scalability: Deep classification in large-scale text hierarchies (GRX, DX, QY, YY), pp. 619–626.
ECMDA-FA-2008-GoldschmidtBU #syntax: Classification of Concrete Textual Syntax Mapping Approaches (TG, SB, AU), pp. 169–184.
SAC-2008-BechiniTV #documentation #ontology: Enabling ontology-based document classification and management in ebXML registries (AB, AT, JV), pp. 1145–1150.
SAC-2008-ChenC #web: Web page genre classification (GC, BC), pp. 2353–2357.
SAC-2008-HanaFOB: Crime scene classification (ROAH, COdAF, LSO, FB), pp. 419–423.
SAC-2008-Hassan #automation #open source: Automated classification of change messages in open source projects (AEH), pp. 837–841.
SAC-2008-LucasCD #fuzzy: General type-2 fuzzy classifiers to land cover classification (LAL, TMC, MRD), pp. 1743–1747.
SAC-2008-MengleG #algorithm #ambiguity #feature model #using: Using ambiguity measure feature selection algorithm for support vector machine classifier (SSRM, NG), pp. 916–920.
SAC-2008-MengleGP #category theory #using: Discovering relationships among categories using misclassification information (SSRM, NG, AP), pp. 932–937.
SAC-2008-NhatL #visualisation: k-means discriminant maps for data visualization and classification (VDMN, SL), pp. 1187–1191.
SAC-2008-NollM #documentation #social #web: Exploring social annotations for web document classification (MGN, CM), pp. 2315–2320.
SAC-2008-RadtkeSW #algorithm #using: Using the RRT algorithm to optimize classification systems for handwritten digits and letters (PVWR, RS, TW), pp. 1748–1752.
SAC-2008-ShaoYN: Strangeness-based feature weighting and classification of gene expression profiles (HS, BY, JHN), pp. 1292–1296.
SAC-2008-SuKZG #collaboration #machine learning #using: Imputation-boosted collaborative filtering using machine learning classifiers (XS, TMK, XZ, RG), pp. 949–950.
PDP-2008-HoferF #fault #grid #multi #taxonomy: A Multi-Perspective Taxonomy for Systematic Classification of Grid Faults (JH, TF), pp. 126–130.
PPoPP-2008-ChengCHT #manycore #platform #scalability #using: Scalable packet classification using interpreting: a cross-platform multi-core solution (HC, ZC, BH, XT), pp. 33–42.
ESOP-2008-KanekoK #linear: Linear Declassification (YK, NK), pp. 224–238.
DocEng-2007-LiSGR #adaptation #categorisation: Adapting associative classification to text categorization (BL, NS, EVG, AR), pp. 205–208.
DRR-2007-JoutelEBE #feature model: Curvelets based feature extraction of handwritten shapes for ancient manuscripts classification (GJ, VE, SB, HE).
ECDL-2007-GiunchigliaZK #algorithm #documentation #formal method: Formalizing the Get-Specific Document Classification Algorithm (FG, IZ, UK), pp. 26–37.
HT-2007-LeveringCY #html #visual notation: Visual features in genre classification of html (RL, MC, LY), pp. 51–52.
HT-2007-WuZM #collaboration #evolution: Collaborative classification of growing collections with evolving facets (HW, MZ, KM), pp. 167–170.
ICDAR-2007-Al-HajjML #recognition #word: Combination of HMM-Based Classifiers for the Recognition of Arabic Handwritten Words (RAHM, CM, LLS), pp. 959–963.
ICDAR-2007-AnBX #documentation: Iterated Document Content Classification (CA, HSB, PX), pp. 252–256.
ICDAR-2007-ChouGC #multi #recognition #using: Recognition of Fragmented Characters Using Multiple Feature-Subset Classifiers (CHC, CYG, FC), pp. 198–202.
ICDAR-2007-Dengel #documentation #learning: Learning of Pattern-Based Rules for Document Classification (AD), pp. 123–127.
ICDAR-2007-FuDLL #effectiveness #recognition: An Effective and Practical Classifier Fusion Strategy for Improving Handwritten Character Recognition (QF, XD, TL, CL), pp. 1038–1042.
ICDAR-2007-HirayamaNK #difference #using: A Classifier of Similar Characters using Compound Mahalanobis Function based on Difference Subspace (JH, HN, NK), pp. 432–436.
ICDAR-2007-Hotta #pattern matching #pattern recognition #recognition: Transform-Invariance in Local Averaging Classifier for Handwritten Digit Pattern Recognition (SH), pp. 347–351.
ICDAR-2007-KalvaEK #image #web: WEB Image Classification Based on the Fusion of Image and Text Classifiers (PRK, FE, ALK), pp. 561–568.
ICDAR-2007-LongJ: Building Compact MQDF Classifier for Off-line Handwritten Chinese Characters by Subspace Distribution Sharing (TL, LJ), pp. 909–913.
ICDAR-2007-NguyenBML #using #verification: Off-line Signature Verification Using Enhanced Modified Direction Features in Conjunction with Neural Classifiers and Support Vector Machines (VN, MB, VM, GL), pp. 734–738.
ICDAR-2007-SilvaN #markov #modelling #performance #visualisation: A Visualization Tool to Improve the Performance of a Classifier Based on Hidden Markov Models (GdS, MN), pp. 1083–1087.
ICDAR-2007-SundaramR #novel #online #recognition: A Novel Hierarchical Classification Scheme for Online Tamil Character Recognition (SS, AR), pp. 1218–1222.
ICDAR-2007-SunHHFN #recognition: Degraded Character Recognition by Complementary Classifiers Combination (JS, KH, YH, KF, SN), pp. 579–583.
ICDAR-2007-ZhouLQA #markov #random: Text/Non-text Ink Stroke Classification in Japanese Handwriting Based on Markov Random Fields (XDZ, CLL, SQ, ÉA), pp. 377–381.
JCDL-2007-KeMF #collaboration #distributed #documentation #learning: Collaborative classifier agents: studying the impact of learning in distributed document classification (WK, JM, YF), pp. 428–437.
JCDL-2007-LiCZL #automation #case study #network #using: Automatic patent classification using citation network information: an experimental study in nanotechnology (XL, HC, ZZ, JL), pp. 419–427.
JCDL-2007-YuTFPFCTC #automation: Automatic syllabus classification (XY, MT, WF, MAPQ, EAF, WC, GT, LNC), pp. 440–441.
ICSM-2007-LuccaFT #concept analysis #using #web: Web Pages Classification using Concept Analysis (GADL, ARF, PT), pp. 385–394.
ILC-2007-Borden #using: Classification using conditional probabilities and Shannon’s definition of information (AB), p. 15.
CIG-2007-AkatsukaS #game studies #learning #video: Reward Allotment Considered Roles for Learning Classifier System For Soccer Video Games (YA, YS), pp. 288–295.
DiGRA-2007-Leino #game studies #sketching: Emotions about the Deniable/Undeniable: Sketch for a Classification of Game Content as Experienced (OTL).
DHM-2007-WangYHWJJLZ #hybrid: A Hybrid AB-RBF Classifier for Surface Electromyography Classification (RW, YY, XH, FW, DJ, XJ, FL, JZ), pp. 727–735.
HCI-AS-2007-LiYG #network #realtime #towards: Traffic Classification — Towards Accurate Real Time Network Applications (ZL, RY, XG), pp. 67–76.
HCI-IPT-2007-LiuS #interactive #visual notation: Interactive Visual Decision Tree Classification (YL, GS), pp. 92–105.
HCI-MIE-2007-ChungK #using: Classification of a Person Picture and Scenery Picture Using Structured Simplicity (MBC, IJK), pp. 821–828.
HCI-MIE-2007-HilligesKPBK #analysis #automation #image #quality #sorting #using: Browsing and Sorting Digital Pictures Using Automatic Image Classification and Quality Analysis (OH, PK, AP, AB, HPK), pp. 882–891.
HCI-MIE-2007-Shirehjini #interactive #multi: A Multidimensional Classification Model for the Interaction in Reactive Media Rooms (AANS), pp. 431–439.
HIMI-MTT-2007-MarucciLC #approach #fuzzy #using: Computer Classification of Injury Narratives Using a Fuzzy Bayes Approach: Improving the Model (HRM, MRL, HLC), pp. 500–506.
HIMI-MTT-2007-NoorinaeiniLW #composition #hybrid: Hybrid Singular Value Decomposition: A Model of Human Text Classification (AN, MRL, SjW), pp. 517–525.
OCSC-2007-CarcilloR #bottom-up #top-down: Tags for Citizens: Integrating Top-Down and Bottom-Up Classification in the Turin Municipality Website (FC, LR), pp. 256–264.
EDOC-2007-Dijkman #difference: A Classification of Differences between Similar BusinessProcesses (RMD), pp. 37–50.
ICEIS-AIDSS-2007-KrohaR #using: Using Grammars for Text Classification (PK, TR), pp. 259–264.
ICEIS-AIDSS-2007-StateCPS #approach: A Connectionist Approach in Bayesian Classification (LS, CC, PV, VS), pp. 185–190.
CIKM-2007-ErtekinHBG #learning: Learning on the border: active learning in imbalanced data classification (SE, JH, LB, CLG), pp. 127–136.
CIKM-2007-FortunaRM #analysis #network #social: Improving the classification of newsgroup messages through social network analysis (BF, EMR, NMF), pp. 877–880.
CIKM-2007-JiangZ #adaptation #approach #statistics: A two-stage approach to domain adaptation for statistical classifiers (JJ, CZ), pp. 401–410.
CIKM-2007-WangL #interactive: Reconstructing ddc for interactive classification (JW, MCL), pp. 137–146.
CIKM-2007-ZhangLYSLM #effectiveness #query #recognition #retrieval: Recognition and classification of noun phrases in queries for effective retrieval (WZ, SL, CTY, CS, FL, WM), pp. 711–720.
ECIR-2007-AyacheQG #multi #semantics: Classifier Fusion for SVM-Based Multimedia Semantic Indexing (SA, GQ, JG), pp. 494–504.
ECIR-2007-BettsMO #information management: The Utility of Information Extraction in the Classification of Books (TB, MM, JO), pp. 295–306.
ECIR-2007-BloehdornM #kernel #semantics: Combined Syntactic and Semantic Kernels for Text Classification (SB, AM), pp. 307–318.
ECIR-2007-HeD #naive bayes #using: Improving Naive Bayes Text Classifier Using Smoothing Methods (FH, XD), pp. 703–707.
ECIR-2007-MeloS #multi #ontology #using: Multilingual Text Classification Using Ontologies (GdM, SS), pp. 541–548.
ECIR-2007-MerkelK #modelling #query: Language Model Based Query Classification (AM, DK), pp. 720–723.
ECIR-2007-NeumayerR #information retrieval #integration #music: Integration of Text and Audio Features for Genre Classification in Music Information Retrieval (RN, AR), pp. 724–727.
ECIR-2007-QuarteroniMMB #ranking: Advanced Structural Representations for Question Classification and Answer Re-ranking (SQ, AM, SM, RB), pp. 234–245.
ICML-2007-AmitFSU #multi: Uncovering shared structures in multiclass classification (YA, MF, NS, SU), pp. 17–24.
ICML-2007-BhattacharyaBC #kernel: Structural alignment based kernels for protein structure classification (SB, CB, NRC), pp. 73–80.
ICML-2007-ChenJ #feature model #set: Minimum reference set based feature selection for small sample classifications (XwC, JCJ), pp. 153–160.
ICML-2007-EspositoR #algorithm #evaluation #named #performance: CarpeDiem: an algorithm for the fast evaluation of SSL classifiers (RE, DPR), pp. 257–264.
ICML-2007-HeraultG #probability: Sparse probabilistic classifiers (RH, YG), pp. 337–344.
ICML-2007-LiaoLC #semistructured data: Quadratically gated mixture of experts for incomplete data classification (XL, HL, LC), pp. 553–560.
ICML-2007-UrtasunD #process: Discriminative Gaussian process latent variable model for classification (RU, TD), pp. 927–934.
ICML-2007-WangZZ #array #hybrid: Hybrid huberized support vector machines for microarray classification (LW, JZ, HZ), pp. 983–990.
ICML-2007-ZhangXSGL #metric: Optimal dimensionality of metric space for classification (WZ, XX, ZS, YFG, HL), pp. 1135–1142.
ICML-2007-ZhangY #consistency #constraints #on the: On the value of pairwise constraints in classification and consistency (JZ, RY), pp. 1111–1118.
KDD-2007-Aggarwal #data type #framework #segmentation: A framework for classification and segmentation of massive audio data streams (CCA), pp. 1013–1017.
KDD-2007-AggarwalY #data type #on the #string: On string classification in data streams (CCA, PSY), pp. 36–45.
KDD-2007-ChaovalitwongseFS #process: Support feature machine for classification of abnormal brain activity (WAC, YJF, RCS), pp. 113–122.
KDD-2007-DaiXYY #clustering #documentation: Co-clustering based classification for out-of-domain documents (WD, GRX, QY, YY), pp. 210–219.
KDD-2007-DasguptaDHJM #feature model: Feature selection methods for text classification (AD, PD, BH, VJ, MWM), pp. 230–239.
KDD-2007-DruckPMZ #generative #hybrid: Semi-supervised classification with hybrid generative/discriminative methods (GD, CP, AM, XZ), pp. 280–289.
KDD-2007-KolczY: Raising the baseline for high-precision text classifiers (AK, WtY), pp. 400–409.
KDD-2007-LuoXLS #distributed #network #peer-to-peer: Distributed classification in peer-to-peer networks (PL, HX, KL, ZS), pp. 968–976.
KDD-2007-SmithE #bias #generative #robust: Making generative classifiers robust to selection bias (ATS, CE), pp. 657–666.
KDD-2007-YanTS #multi: Model-shared subspace boosting for multi-label classification (RY, JT, JRS), pp. 834–843.
MLDM-2007-CoenenLSW #identification #statistics: Statistical Identification of Key Phrases for Text Classification (FC, PHL, RS, YJW), pp. 838–853.
MLDM-2007-EkdahlK #learning #on the: On Concentration of Discrete Distributions with Applications to Supervised Learning of Classifiers (ME, TK), pp. 2–16.
MLDM-2007-Kertesz-FarkasKP #equivalence #learning: Equivalence Learning in Protein Classification (AKF, AK, SP), pp. 824–837.
MLDM-2007-MartinsSSPG #image #using: Classification of Breast Masses in Mammogram Images Using Ripley’s K Function and Support Vector Machine (LdOM, ECdS, ACS, ACdP, MG), pp. 784–794.
MLDM-2007-ShidaraNK #consistency #named: CCIC: Consistent Common Itemsets Classifier (YS, AN, MK), pp. 490–498.
MLDM-2007-SzepannekBW #on the: On the Combination of Locally Optimal Pairwise Classifiers (GS, BB, CW), pp. 104–116.
MLDM-2007-WangLYC #data type #fuzzy #incremental #mining: An Incremental Fuzzy Decision Tree Classification Method for Mining Data Streams (TW, ZL, YY, HC), pp. 91–103.
MLDM-2007-WangXC #approach #mining #novel: A Novel Rule Ordering Approach in Classification Association Rule Mining (YJW, QX, FC), pp. 339–348.
MLDM-2007-YuL #approach #graph #named: PE-PUC: A Graph Based PU-Learning Approach for Text Classification (SY, CL), pp. 574–584.
RecSys-2007-PronkVPT #naive bayes #recommendation: Incorporating user control into recommender systems based on naive bayesian classification (VP, WFJV, AP, MT), pp. 73–80.
SEKE-2007-AlencarRSF #modelling #probability #project management: Combining Decorated Classification Trees with RCPS Stochastic Models to Gain New Valuable Insights into Software Project Management (AJA, GGR, EAS, ALF), pp. 151–156.
SEKE-2007-CordeiroGES #constraints #database #design #version control: A Deep Classification of Temporal Versioned Integrity Constraints for Designing Database Applications (RLFC, RdMG, NE, CSdS), pp. 416–421.
SEKE-2007-DongZ #design pattern: Classification of Design Pattern Traits (JD, YZ), p. 473–?.
SEKE-2007-LiZXS #component #generative #ontology #retrieval: Ontology Based Classification Generating Method for Browsing-Based Component Retrieval (GL, LZ, BX, WS), p. 428–?.
SIGIR-2007-BeitzelJCF #query #topic #web: Varying approaches to topical web query classification (SMB, ECJ, AC, OF), pp. 783–784.
SIGIR-2007-BroderFGJJZ #query #robust #using #web: Robust classification of rare queries using web knowledge (AZB, MF, EG, AJ, VJ, TZ), pp. 231–238.
SIGIR-2007-FanGL #automation #image: Hierarchical classification for automatic image annotation (JF, YG, HL), pp. 111–118.
SIGIR-2007-HuDGX #documentation #locality: Locality discriminating indexing for document classification (JH, WD, JG, WX), pp. 689–690.
SIGIR-2007-KyriakopoulouK #clustering #using: Using clustering to enhance text classification (AK, TK), pp. 805–806.
SIGIR-2007-OlssonO: Improving text classification for oral history archives with temporal domain knowledge (JSO, DWO), pp. 623–630.
SIGIR-2007-StaffB #automation #category theory #web: Automatic classification of web pages into bookmark categories (CS, IB), pp. 731–732.
SIGIR-2007-StepinskiM: A fact/opinion classifier for news articles (AS, VOM), pp. 807–808.
SIGIR-2007-ZhangL #semantics: Semantic text classification of disease reporting (YZ, BL), pp. 747–748.
SIGIR-2007-ZhuYCG #matrix #using: Combining content and link for classification using matrix factorization (SZ, KY, YC, YG), pp. 487–494.
SAC-2007-Cardoso-CachopoO #categorisation #using: Semi-supervised single-label text categorization using centroid-based classifiers (ACC, ALO), pp. 844–851.
SAC-2007-LeeOSYT #automation: Automatic classification of digestive organs in wireless capsule endoscopy videos (JL, JHO, SKS, XY, SJT), pp. 1041–1045.
SAC-2007-TanC #using: Using hypothesis margin to boost centroid text classifier (ST, XC), pp. 398–403.
SAC-2007-VanderleiDMGAM #component #retrieval: A cooperative classification mechanism for search and retrieval software components (TAV, FAD, ACM, VCG, ESdA, SRdLM), pp. 866–871.
SAC-2007-XiongCL #database #mining #multi #using: Mining multiple private databases using a kNN classifier (LX, SC, LL), pp. 435–440.
SAC-2007-ZengWN #analysis: Text classification based on partial least square analysis (XQZ, MWW, JYN), pp. 834–838.
CASE-2007-ChenT #gesture #multi #recognition: Multiple-angle Hand Gesture Recognition by Fusing SVM Classifiers (YTC, KTT), pp. 527–530.
CASE-2007-McVittieSMMLHM #automation #using: Automated Classification of Macrophage Membrane Integrity using a Fluorescent Live/Dead Stain (PM, CSS, TWM, SM, MEL, MH, DRM), pp. 554–559.
DATE-2007-NarayananHMCZ #implementation #interactive: Interactive presentation: An FPGA implementation of decision tree classification (RN, DH, GM, ANC, JZ), pp. 189–194.
ESOP-2007-MantelR #security #what: Controlling the What and Where of Declassification in Language-Based Security (HM, AR), pp. 141–156.
DocEng-2006-SimskeWS #documentation: Meta-algorithmic systems for document classification (SJS, DWW, MS), pp. 98–106.
DRR-2006-AndraZ #consistency #nearest neighbour: Style consistent nearest neighbor classifier (SA, XZ).
DRR-2006-AsSadhanBSN #comparative #evaluation #recognition #robust: Comparative evaluation of different classifiers for robust distorted-character recognition (BA, ZAB, AES, MN).
DRR-2006-ChellapillaSS: Optimally combining a cascade of classifiers (KC, MS, PYS).
ECDL-2006-GolubAMG #automation: Comparing and Combining Two Approaches to Automated Subject Classification of Text (KG, AA, DM, MG), pp. 467–470.
ECDL-2006-KimR #automation #metadata: Genre Classification in Automated Ingest and Appraisal Metadata (YK, SR), pp. 63–74.
JCDL-2006-CoutoCGCZMR #case study #comparative #documentation: A comparative study of citations and links in document classification (TC, MC, MAG, PC, NZ, ESdM, BARN), pp. 75–84.
SCAM-2006-PanKW #debugging #metric #slicing #using: Bug Classification Using Program Slicing Metrics (KP, SK, EJWJ), pp. 31–42.
ICEIS-J-2006-Leukel06a #approach #data transformation: Controlling Property Growth in Product Classification Schemes: A Data Management Approach (JL), pp. 363–374.
ICEIS-SAIC-2006-Leukel #library #maintenance: Maintaining Property Libraries in Product Classification Schemes (JL), pp. 3–10.
CIKM-2006-AnagnostopoulosBP #effectiveness #performance: Effective and efficient classification on a search-engine model (AA, AZB, KP), pp. 208–217.
CIKM-2006-AssfalgBK #3d #kernel #named #string: 3DString: a feature string kernel for 3D object classification on voxelized data (JA, KMB, HPK), pp. 198–207.
CIKM-2006-OlssonO: Combining feature selectors for text classification (JSO, DWO), pp. 798–799.
CIKM-2006-SchutzeVP #performance: Performance thresholding in practical text classification (HS, EV, JOP), pp. 662–671.
CIKM-2006-ShenSYC #modelling #multi: Text classification improved through multigram models (DS, JTS, QY, ZC), pp. 672–681.
CIKM-2006-VelosoMCGZ #documentation #lazy evaluation #multi: Multi-evidence, multi-criteria, lazy associative document classification (AV, WMJ, MC, MAG, MJZ), pp. 218–227.
CIKM-2006-XiongCL #database #multi #nearest neighbour: k nearest neighbor classification across multiple private databases (LX, SC, LL), pp. 840–841.
CIKM-2006-XuWFSP #correlation #data type: Classification spanning correlated data streams (YX, KW, AWCF, RS, JP), pp. 132–141.
ECIR-2006-BoumaR: Specificity Helps Text Classification (LB, MdR), pp. 539–542.
ECIR-2006-DemartiniM #effectiveness #information retrieval #metric: A Classification of IR Effectiveness Metrics (GD, SM), pp. 488–491.
ECIR-2006-KeBO #email #named: PERC: A Personal Email Classifier (SWK, CB, MPO), pp. 460–463.
ECIR-2006-YinP #adaptation #naive bayes #rank: Adapting the Naive Bayes Classifier to Rank Procedural Texts (LY, RP), pp. 179–190.
ICML-2006-Cesa-BianchiGZ: Hierarchical classification: combining Bayes with SVM (NCB, CG, LZ), pp. 177–184.
ICML-2006-DaiYTK #adaptation #nondeterminism: Locally adaptive classification piloted by uncertainty (JD, SY, XT, JTK), pp. 225–232.
ICML-2006-DenisMR #learning #naive bayes #performance: Efficient learning of Naive Bayes classifiers under class-conditional classification noise (FD, CNM, LR), pp. 265–272.
ICML-2006-GravesFGS #network #sequence: Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks (AG, SF, FJG, JS), pp. 369–376.
ICML-2006-HertzBW #kernel #learning: Learning a kernel function for classification with small training samples (TH, ABH, DW), pp. 401–408.
ICML-2006-HoiJZL #image #learning: Batch mode active learning and its application to medical image classification (SCHH, RJ, JZ, MRL), pp. 417–424.
ICML-2006-KimMSBL #linear: Pareto optimal linear classification (SJK, AM, SS, SPB, JL), pp. 473–480.
ICML-2006-LeeGW #using: Using query-specific variance estimates to combine Bayesian classifiers (CHL, RG, SW), pp. 529–536.
ICML-2006-ReyzinS #complexity #how: How boosting the margin can also boost classifier complexity (LR, RES), pp. 753–760.
ICML-2006-SinghiL #bias #learning #set: Feature subset selection bias for classification learning (SKS, HL), pp. 849–856.
ICML-2006-SuZ #network: Full Bayesian network classifiers (JS, HZ), pp. 897–904.
ICML-2006-XiKSWR #performance #reduction #using: Fast time series classification using numerosity reduction (XX, EJK, CRS, LW, CAR), pp. 1033–1040.
ICPR-v1-2006-ArandjelovicC #set #using: Face Set Classification using Maximally Probable Mutual Modes (OA, RC), pp. 511–514.
ICPR-v1-2006-ArzhaevaGT #detection #distance #image: Image Classification from Generalized Image Distance Features: Application to Detection of Interstitial Disease in Chest Radiographs (YA, BvG, DMJT), pp. 367–370.
ICPR-v1-2006-BoschMOM #approach #question #what: Object and Scene Classification: what does a Supervised Approach Provide us? (AB, XM, AO, RM), pp. 773–777.
ICPR-v1-2006-ConduracheA #2d #image #linear #segmentation #using: Vessel Segmentation in 2D-Projection Images Using a Supervised Linear Hysteresis Classifier (AC, TA), pp. 343–346.
ICPR-v1-2006-FuCLR #feature model #image: Boosted Band Ratio Feature Selection for Hyperspectral Image Classification (ZF, TC, NL, ARK), pp. 1059–1062.
ICPR-v1-2006-KaufholdCHR #recognition #segmentation #using: Recognition and Segmentation of Scene Content using Region-Based Classification (JPK, RC, AH, PR), pp. 755–760.
ICPR-v1-2006-KimK #using: Simultaneous Classification and VisualWord Selection using Entropy-based Minimum Description Length (SK, ISK), pp. 650–653.
ICPR-v1-2006-MarmoAC #set #using: Microfossils shape classification using a set of width values (RM, SA, VC), pp. 691–694.
ICPR-v1-2006-NegriCMP #algorithm: An Oriented-Contour Point Based Voting Algorithm for Vehicle Type Classification (PN, XC, MM, RP), pp. 574–577.
ICPR-v1-2006-PrehnS #adaptation #algorithm #clustering #incremental #robust #using: An Adaptive Classification Algorithm Using Robust Incremental Clustering (HP, GS), pp. 896–899.
ICPR-v1-2006-SunSM #simulation: The Role of Featural and Configural Information in Face Classification A Simulation of the Expertise Hypothesis (YS, NS, MM), pp. 1166–1170.
ICPR-v1-2006-ThurauHB #behaviour #game studies #video: Classification of Team Behaviors in Sports Video Games (CT, TH, CB), pp. 1188–1191.
ICPR-v1-2006-WongC #gesture #recognition #using: Continuous Gesture Recognition using a Sparse Bayesian Classifier (SFW, RC), pp. 1084–1087.
ICPR-v1-2006-WongLI: Brush Writing Style Classification from Individual Chinese Characters (STSW, HL, HHSI), pp. 884–887.
ICPR-v1-2006-ZhangLSC #corpus #performance: An Efficient SVM Classifier for Lopsided Corpora (XZ, BCL, WS, LC), pp. 1144–1147.
ICPR-v1-2006-ZhuWCW #human-computer #interface #predict: GMM-Based Classification Method for Continuous Prediction in Brain-Computer Interface (XZ, JW, YC, YW), pp. 1171–1174.
ICPR-v2-2006-ArivazhaganGK #statistics #using: Texture classification using Curvelet Statistical and Co-occurrence Features (SA, LG, TGSK), pp. 938–941.
ICPR-v2-2006-BertolamiB #integration #multi #recognition: Early feature stream integration versus decision level combination in a multiple classifier system for text line recognition (RB, HB), pp. 845–848.
ICPR-v2-2006-BhuiyanN #detection #image #using: Anti-personnel Mine Detection and Classification Using GPR Image (AB, BN), pp. 1082–1085.
ICPR-v2-2006-ChenB #invariant #using: Invariant Texture Classification Using Ridgelet Packets (GC, PB), pp. 464–467.
ICPR-v2-2006-ChiangK #using: Classification of Line and Character Pixels on Raster Maps Using Discrete Cosine Transformation Coefficients and Support Vector Machine (YYC, CAK), pp. 1034–1037.
ICPR-v2-2006-ChoiLY #feature model #using: Feature Extraction for Bank Note Classification Using Wavelet Transform (EC, JL, JY), pp. 934–937.
ICPR-v2-2006-DengHG #algorithm: Ada-Boost Algorithm, Classification, Naïve- (WD, JH, JG), pp. 699–702.
ICPR-v2-2006-DonateDR: Classification of Textures Distorted by WaterWaves (AD, GD, ER), pp. 421–424.
ICPR-v2-2006-Ekbal #predict #using: Improvement of Prediction Accuracy Using Discretization and Voting Classifier (AE), pp. 695–698.
ICPR-v2-2006-FangQ: Car/Non-Car Classification in an Informative Sample Subspace (JF, GQ), pp. 962–965.
ICPR-v2-2006-GaoLL #approach #learning #optimisation: An ensemble classifier learning approach to ROC optimization (SG, CHL, JHL), pp. 679–682.
ICPR-v2-2006-GuptaRPH: Classifiers for Motion (MDG, SR, NP, TSH), pp. 593–596.
ICPR-v2-2006-Hotta #adaptation: Adaptive Weighting of Local Classifiers by Particle Filter (KH), pp. 610–613.
ICPR-v2-2006-HuD #multi #theorem: A “No Panacea Theorem” for Multiple Classifier Combination (RH, RID), pp. 1250–1253.
ICPR-v2-2006-IlonenPKK: Gaussian mixture pdf in one-class classification: computing and utilizing confidence values (JI, PP, JKK, HK), pp. 577–580.
ICPR-v2-2006-KelmPM #generative #learning #multi: Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning (BMK, CP, AM), pp. 828–832.
ICPR-v2-2006-KennedyNS: An LVQ-based Automotive Occupant Classification System (KRK, JFN, MS), pp. 662–665.
ICPR-v2-2006-LefebvreLRG #comparison #image #process: Supervised Image Classification by SOM Activity Map Comparison (GL, CL, JR, CG), pp. 728–731.
ICPR-v2-2006-LernerM #image #learning #network: Learning Bayesian Networks for Cytogenetic Image Classification (BL, RM), pp. 772–775.
ICPR-v2-2006-Liu #feature model #polynomial #recognition #using: High Accuracy Handwritten Chinese Character Recognition Using Quadratic Classifiers with Discriminative Feature Extraction (CLL), pp. 942–945.
ICPR-v2-2006-LiuL #image #using: Genus-Zero Shape Classification Using Spherical Normal Image (SL, JL), pp. 126–129.
ICPR-v2-2006-McDanielKP #approach #visual notation: A Bayesian Approach to Visual Size Classification of Everyday Objects (TLM, KK, SP), pp. 255–259.
ICPR-v2-2006-NandedkarB #fuzzy #network: A Reflex Fuzzy Min Max Neural Network for Granular Data Classification (AVN, PKB), pp. 650–653.
ICPR-v2-2006-QinWHG #automation: Unsupervised Texture Classification: Automatically Discover and Classify Texture Patterns (LQ, WW, QH, WG), pp. 433–436.
ICPR-v2-2006-Sarkar #image #visual notation: Image classification: Classifying distributions of visual features (PS), pp. 472–475.
ICPR-v2-2006-ShimshoniRS #image #performance #verification: Efficient Search and Verification for Function Based Classification from Real Range Images (IS, ER, OS), pp. 1118–1121.
ICPR-v2-2006-SuSCG #recognition: Patch-Based Gabor Fisher Classifier for Face Recognition (YS, SS, XC, WG), pp. 528–531.
ICPR-v2-2006-ThakoorJWG: Occlusion Resistant Shape Classifier based onWarped Optimal Path Matching (NT, SJ, QW, JG), pp. 60–63.
ICPR-v2-2006-TsuchiyaF #visual notation: Evaluating Feature Importance for Object Classification in Visual Surveillance (MT, HF), pp. 978–981.
ICPR-v2-2006-UekiHK #2d #analysis #linear: Two-dimensional Heteroscedastic Linear Discriminant Analysis for Age-group Classification (KU, TH, TK), pp. 585–588.
ICPR-v2-2006-WimmerRB #approach: A Person and Context Specific Approach for Skin Color Classification (MW, BR, MB), pp. 39–42.
ICPR-v2-2006-YaslanC #feature model #music #using: Audio Music Genre Classification Using Different Classifiers and Feature Selection Methods (YY, ZÇ), pp. 573–576.
ICPR-v2-2006-YuanQYZ #approach #kernel: An Approach for Constructing Sparse Kernel Classifier (ZY, YQ, YY, NZ), pp. 560–563.
ICPR-v2-2006-ZhangC #locality: Comparing Different Localization Approaches of the Radon Transform for Road Centerline Extraction from Classified Satellite Imagery (QZ, IC), pp. 138–141.
ICPR-v2-2006-ZhangPB #learning #representation: Learning Optimal Filter Representation for Texture Classification (PZ, JP, BPB), pp. 1138–1141.
ICPR-v2-2006-ZhengYYW #effectiveness #image #problem: Effective classification image space which can solve small sample size problem (YJZ, JYY, JY, XW), pp. 861–864.
ICPR-v3-2006-AbdulkaderDZ #comparative: Comparative Classifier Aggregation (AA, JAD, QZ), pp. 156–159.
ICPR-v3-2006-AnLV #performance: Efficient Cross-validation of the Complete Two Stages in KFD Classifier Formulation (SA, WL, SV), pp. 240–244.
ICPR-v3-2006-ArreolaFB #linear #performance #using: Fast Support Vector Machine Classification using linear SVMs (KZA, JF, HB), pp. 366–369.
ICPR-v3-2006-BarbuRLAHT #algorithm #graph #recognition #search-based #using: Graph Classification Using Genetic Algorithm and Graph Probing Application to Symbol Recognition (EB, RR, HL, SA, PH, ÉT), pp. 296–299.
ICPR-v3-2006-BauckhageK06a #multi: Benefits of Separable, Multilinear Discriminant Classification (CB, TK), pp. 1240–1243.
ICPR-v3-2006-BeveridgeSR #comparison #detection #naive bayes #using: A Comparison of Pixel, Edge andWavelet Features for Face Detection using a Semi-Naive Bayesian Classifier (JRB, JS, BR), pp. 1175–1178.
ICPR-v3-2006-HarmoucheCAFA #modelling: Bayesian MS Lesion Classification Modeling Regional and Local Spatial Information (RH, DLC, DLA, SJF, TA), pp. 984–987.
ICPR-v3-2006-HuS06a #clustering #functional #image #normalisation: Normalization of Functional Magnetic Resonance Images by Classified Cerebrospinal Fluid Cluster (ZH, PS), pp. 938–941.
ICPR-v3-2006-JiaZHW: Gaussian Weighted Histogram Intersection for License Plate Classification (WJ, HZ, XH, QW), pp. 574–577.
ICPR-v3-2006-KierA #multi #predict: Predicting the benefit of sample size extension in multiclass k-NN classification (CK, TA), pp. 332–335.
ICPR-v3-2006-KovalevP: The Classification Gradient (VAK, MP), pp. 830–833.
ICPR-v3-2006-LeeP #detection #robust: Robust vehicle detection based on shadow classification (DL, YP), pp. 1167–1170.
ICPR-v3-2006-LernerV #fuzzy #image #search-based #using: Image Classification for Genetic Diagnosis using Fuzzy ARTMAP (BL, BV), pp. 362–365.
ICPR-v3-2006-LiC #nearest neighbour #probability #using: Classification Using the Local Probabilistic Centers of k-Nearest Neighbors (BYL, YWC), pp. 1220–1223.
ICPR-v3-2006-LouJ #adaptation #nearest neighbour #novel: Novel Adaptive Nearest Neighbor Classifiers Based On Hit-Distance (ZL, ZJ), pp. 87–90.
ICPR-v3-2006-Martinez-ArroyoS #learning #naive bayes: Learning an Optimal Naive Bayes Classifier (MMA, LES), pp. 1236–1239.
ICPR-v3-2006-MatosC #network: Combining global and local classifiers with Bayesian network (LNM, JMdC), pp. 1212–1215.
ICPR-v3-2006-NagasakiMKS #adaptation #image: A Coupon Classification Method Based on Adaptive Image Vector Matching (TN, KM, TK, HS), pp. 280–283.
ICPR-v3-2006-PaclikND #image #similarity: A Trainable Similarity Measure for Image Classification (PP, JN, RPWD), pp. 391–394.
ICPR-v3-2006-PekalskaD: Dissimilarity-based classification for vectorial representations (EP, RPWD), pp. 137–140.
ICPR-v3-2006-TscherepanowZK #image: Classification of Segmented Regions in Brightfield Microscope Images (MT, FZ, FK), pp. 972–975.
ICPR-v3-2006-Wang06b #image: Colony Delineation on Image Classification (WW), pp. 705–708.
ICPR-v3-2006-WangNC #approach: A Minimum Sphere Covering Approach to Pattern Classification (JW, PN, LNC), pp. 433–436.
ICPR-v3-2006-WongLY #performance: Improving Text Classifier Performance based on AUC (AKSW, JWTL, DSY), pp. 268–271.
ICPR-v3-2006-WongWC #robust #using: Robust Appearance-based Tracking using a sparse Bayesian classifier (SFW, KYKW, RC), pp. 47–50.
ICPR-v3-2006-XuanCZYHSF #analysis #component #novel: A Novel Pattern Classification Scheme: Classwise Non-Principal Component Analysis (CNPCA) (GX, PC, XZ, QY, CH, YQS, DF), pp. 320–323.
ICPR-v3-2006-YangLA #automation #case study #gender: An Experimental Study on Automatic Face Gender Classification (ZY, ML, HA), pp. 1099–1102.
ICPR-v3-2006-YinNFMA #statistics: Statistical Model for the Classification of the Wavelet Transforms of T-ray Pulses (XXY, BWHN, BF, SPM, DA), pp. 236–239.
ICPR-v3-2006-YuHSLPGF: Shape-based Discrimination and Classification of Cortical Surfaces (PY, XH, FS, AKL, RAP, PG, BF), pp. 445–448.
ICPR-v3-2006-ZhangR06a #integration #robust #visual notation: Robust Visual Tracking via Pixel Classification and Integration (CZ, YR), pp. 37–42.
ICPR-v3-2006-ZouB #energy #image #process #programming #search-based: Human Activity Classification Based on Gait Energy Image and Coevolutionary Genetic Programming (XZ, BB), pp. 556–559.
ICPR-v4-2006-AndraN: Combining Dichotomizers for MAP Field Classification (SA, GN), pp. 210–214.
ICPR-v4-2006-BauckhageK06b #multi: Benefits of Separable, Multilinear Discriminant Classification (CB, TK), p. 959.
ICPR-v4-2006-Fisher06a #capacity #empirical: An Empirical Model for Saturation and Capacity in Classifier Spaces (RBF), pp. 189–193.
ICPR-v4-2006-JinYSLX #detection #hybrid #precise #robust: A hybrid classifier for precise and robust eye detection (LJ, XHY, SS, JL, LX), pp. 731–735.
ICPR-v4-2006-LefaucheurN #multi #robust #symmetry: Robust Multiclass Ensemble Classifiers via Symmetric Functions (PL, RN), pp. 136–139.
ICPR-v4-2006-LiaoS: Classification of Audio Signals in All-Night Sleep Studies (WHL, YSS), pp. 302–305.
ICPR-v4-2006-LiC06a #nearest neighbour #probability #using: Classification Using the Local Probabilistic Centers of k-Nearest Neighbors (BYL, YWC), p. 954.
ICPR-v4-2006-Martinez-ArroyoS06a #learning #naive bayes: Learning an Optimal Naive Bayes Classifier (MMA, LES), p. 958.
ICPR-v4-2006-MatosC06a #network: Combining global and local classifiers with Bayesian network (LNM, JMdC), p. 952.
ICPR-v4-2006-OliverMMBF #approach: A new approach to the classification of mammographic masses and normal breast tissue (AO, JM, RM, AB, JF), pp. 707–710.
ICPR-v4-2006-PhamS #approximate #clustering #metric #performance: Metric tree partitioning and Taylor approximation for fast support vector classification (TVP, AWMS), pp. 132–135.
ICPR-v4-2006-TiviveB #gender #network: A Shunting Inhibitory Convolutional Neural Network for Gender Classification (FHCT, AB), pp. 421–424.
ICPR-v4-2006-TodorovicA #3d #segmentation #using: 3D Texture Classification Using the Belief Net of a Segmentation Tree (ST, NA), pp. 33–36.
ICPR-v4-2006-Wang06d #metric #process #profiling: From Blob Metrics to Posture Classification to Activity Profiling (LW0), pp. 736–739.
ICPR-v4-2006-WangWLJK #analysis #component #independence #using: Content-Based Audio Classification Using Support Vector Machines and Independent Component Analysis (JCW, JFW, CBL, KTJ, WHK), pp. 157–160.
ICPR-v4-2006-WangXC #2d #automation #pseudo #using #video: Automatic Sports Video Genre Classification using Pseudo-2D-HMM (JW, CX, EC), pp. 778–781.
ICPR-v4-2006-WongN: Blind Phase-Amplitude Modulation Classification with Unknown Phase Offset (MLDW, AKN), pp. 177–180.
ICPR-v4-2006-XuC #invariant #multi: Multiscale Blob Features for Gray Scale, Rotation and Spatial Scale Invariant Texture Classification (QX, YQC), pp. 29–32.
KDD-2006-ArunasalamC #named #top-down: CCCS: a top-down associative classifier for imbalanced class distribution (BA, SC), pp. 517–522.
KDD-2006-BiPOKFSR #detection #symmetry: Computer aided detection via asymmetric cascade of sparse hyperplane classifiers (JB, SP, KO, TK, GF, MS, RBR), pp. 837–844.
KDD-2006-BurkeMWB #collaboration #detection #recommendation: Classification features for attack detection in collaborative recommender systems (RDB, BM, CW, RB), pp. 542–547.
KDD-2006-CastanoMTGDCCD #detection: Onboard classifiers for science event detection on a remote sensing spacecraft (RC, DM, NT, RG, TD, BC, SAC, AD), pp. 845–851.
KDD-2006-FanD #bias #framework #performance #testing: Reverse testing: an efficient framework to select amongst classifiers under sample selection bias (WF, ID), pp. 147–156.
KDD-2006-Forman #fault #roadmap: Quantifying trends accurately despite classifier error and class imbalance (GF), pp. 157–166.
KDD-2006-HoiLC #kernel #learning: Learning the unified kernel machines for classification (SCHH, MRL, EYC), pp. 187–196.
KDD-2006-NathBM #approach #clustering #scalability #using: Clustering based large margin classification: a scalable approach using SOCP formulation (JSN, CB, MNM), pp. 674–679.
KDD-2006-TangZL #data-driven #semantics #taxonomy: Acclimatizing taxonomic semantics for hierarchical content classification from semantics to data-driven taxonomy (LT, JZ, HL), pp. 384–393.
KDD-2006-WeiK: Semi-supervised time series classification (LW, EJK), pp. 748–753.
KDD-2006-YanB #optimisation #ranking: Beyond classification and ranking: constrained optimization of the ROI (LY, PB), pp. 948–953.
KDD-2006-ZhangL #string: Extracting key-substring-group features for text classification (DZ, WSL), pp. 474–483.
SEKE-2006-ZengA #multi #representation: Classification by Multi-Perspective Representation Method (JZ, RA), pp. 85–90.
SIGIR-2006-AngelovaW #graph: Graph-based text classification: learn from your neighbors (RA, GW), pp. 485–492.
SIGIR-2006-BlunsomKC #modelling: Question classification with log-linear models (PB, KK, JRC), pp. 615–616.
SIGIR-2006-DayanikLMMG: Constructing informative prior distributions from domain knowledge in text classification (AAD, DDL, DM, VM, AG), pp. 493–500.
SIGIR-2006-Olsson #analysis #set: An analysis of the coupling between training set and neighborhood sizes for the kNN classifier (JSO), pp. 685–686.
SIGIR-2006-ShenSYC #query #web: Building bridges for web query classification (DS, JTS, QY, ZC), pp. 131–138.
SIGIR-2006-SteinAF #fault: The effect of OCR errors on stylistic text classification (SSS, SA, OF), pp. 701–702.
QAPL-2005-LanotteMT06 #probability #security: A Classification of Time and/or Probability Dependent Security Properties (RL, AMS, AT), pp. 177–193.
RE-2006-Cleland-HuangSZS #aspect-oriented #detection #non-functional #requirements: The Detection and Classification of Non-Functional Requirements with Application to Early Aspects (JCH, RS, XZ, PS), pp. 36–45.
ASE-2006-dAmorimPXME #automation #comparison #empirical #generative #object-oriented #testing: An Empirical Comparison of Automated Generation and Classification Techniques for Object-Oriented Unit Testing (Md, CP, TX, DM, MDE), pp. 59–68.
FSE-2006-StorzerRRT #java #source code #using: Finding failure-inducing changes in java programs using change classification (MS, BGR, XR, FT), pp. 57–68.
ICSE-2006-AbeMKKH #estimation #using: Estimation of project success using Bayesian classifier (SA, OM, TK, NK, MH), pp. 600–603.
SAC-2006-AbidinP #data mining #mining #named #nearest neighbour #performance #scalability: SMART-TV: a fast and scalable nearest neighbor based classifier for data mining (TA, WP), pp. 536–540.
SAC-2006-BelsisFGS: SF-HME system: a hierarchical mixtures-of-experts classification system for spam filtering (PB, KF, SG, CS), pp. 354–360.
SAC-2006-CraigL #learning #using: Protein classification using transductive learning on phylogenetic profiles (RAC, LL), pp. 161–166.
SAC-2006-FelipeRSTT #effectiveness #retrieval: Effective shape-based retrieval and classification of mammograms (JCF, MXR, EPMdS, AJMT, CTJ), pp. 250–255.
SAC-2006-Ferrer-TroyanoAS #data type #incremental #learning: Data streams classification by incremental rule learning with parameterized generalization (FJFT, JSAR, JCRS), pp. 657–661.
SAC-2006-ForteSP #internet: A content classification and filtering server for the internet (MF, WLdS, AFdP), pp. 1166–1171.
SAC-2006-MerschmannP #approach: A Bayesian approach for protein classification (LHdCM, AP), pp. 200–201.
SAC-2006-TailbyDMS #automation #email: Email classification for automated service handling (RT, RD, BM, DS), pp. 1073–1077.
SAC-2006-XingMXV #documentation #edit distance #xml: Computing edit distances between an XML document and a schema and its application in document classification (GX, CRM, ZX, SDV), pp. 831–835.
SAC-2006-ZamolotskikhDC #bias: A methodology for comparing classifiers that allow the control of bias (AZ, SJD, PC), pp. 582–587.
DATE-2006-IgnatNSN #impact analysis #operating system #realtime: Soft-error classification and impact analysis on real-time operating systems (NI, BN, YS, GN), pp. 182–187.
DATE-2006-KruppM #functional #random testing #testing: Classification trees for random tests and functional coverage (AK, WM), pp. 1031–1032.
DATE-DF-2006-PapaefstathiouP: A hardware-engine for layer-2 classification in low-storage, ultra-high bandwidth environments (VP, IP), pp. 112–117.
MBT-2006-ConradK #embedded: An Extension of the Classification-Tree Method for Embedded Systems for the Description of Events (MC, AK), pp. 3–11.
DocEng-2005-SimskeLA #image #statistics: A statistical method for binary classification of images (SJS, DL, JSA), pp. 127–129.
ECDL-2005-BalkeNST #distributed #documentation #retrieval: DL Meets P2P — Distributed Document Retrieval Based on Classification and Content (WTB, WN, WS, UT), pp. 379–390.
ECDL-2005-GolubA #automation #html #metadata: Importance of HTML Structural Elements and Metadata in Automated Subject Classification (KG, AA), pp. 368–378.
ECDL-2005-KimJC #automation #library #naive bayes #ontology #semantics: Building Semantic Digital Libraries: Automated Ontology Linking by Associative Naïve Bayes Classifier (HK, MGJ, SSC), pp. 500–501.
ICDAR-2005-BhagvatiD #using: Classification of Liquid and Viscous Inks using HSV Colour Space (CB, HD), pp. 660–664.
ICDAR-2005-BhattacharyaC #recognition: Fusion of Combination Rules of an Ensemble of MLP Classifiers for Improved Recognition Accuracy of Handprinted Bangla Numerals (UB, BBC), pp. 322–326.
ICDAR-2005-DuongE #design #recognition: Cascade Classifier : Design and Application to Digit Recognition (JD, HE), pp. 1065–1069.
ICDAR-2005-FarahEKS #multi #recognition #word: Benefit of multiclassifier systems for Arabic handwritten words recognition (NF, AE, TK, MS), pp. 222–226.
ICDAR-2005-FengM #modelling #recognition: Classification Models for Historical Manuscript Recognition (SF, RM), pp. 528–532.
ICDAR-2005-IshitaniFS #analysis #documentation #xml: Table Structure Analysis Based on Cell Classification and Cell Modification for XML Document Transformation (YI, KF, KS), pp. 1247–1252.
ICDAR-2005-KangD #multi: Selection of Classifiers for the Construction of Multiple Classifier Systems (HJK, DSD), pp. 1194–1198.
ICDAR-2005-LeiG #sequence: Similarity-driven Sequence Classification Based on Support Vector Machines (HL, VG), pp. 252–261.
ICDAR-2005-LiuD #multi #polynomial #recognition #using: Handwritten Character Recognition Using Gradient Feature and Quadratic Classifier with Multiple Discrimination Schemes (HL, XD), pp. 19–25.
ICDAR-2005-LiuMK #feature model #recognition #scalability #set #using: Building Compact Classifier for Large Character Set Recognition Using Discriminative Feature Extraction (CLL, RM, MK), pp. 846–850.
ICDAR-2005-LiuWD #detection #image: Text Detection in Images Based on Unsupervised Classification of Edge-based Features (CL, CW, RD), pp. 610–614.
ICDAR-2005-MoussaZAB: Can Fractal Dimension Be Used In Font Classification (SBM, AZ, AMA, AB), pp. 146–150.
ICDAR-2005-OliveiraBS05a #optimisation: Improving Cascading Classifiers with Particle Swarm Optimization (LSO, AdSBJ, RS), pp. 570–574.
ICDAR-2005-PrudentE #multi: A Toplogy Based Multi-Classifier System (YP, AE), pp. 670–674.
ICDAR-2005-RadtkeSW #feature model: Intelligent Feature Extraction for Ensemble of Classifiers (PVWR, RS, TW), pp. 866–870.
ICDAR-2005-WangC #using: A Hierarchical Classifier Using New Support Vector Machine (YCFW, DC), pp. 851–855.
JCDL-2005-FuKM #automation #framework #multi #using: Automated text classification using a multi-agent framework (YF, WK, JM), pp. 157–158.
VLDB-2005-LimWV #estimation #online #string #xml: CXHist : An On-line Classification-Based Histogram for XML String Selectivity Estimation (LL, MW, JSV), pp. 1187–1198.
VLDB-2005-MeierWAS #fuzzy #query #using: Using a Fuzzy Classification Query Language for Customer Relationship Management (AM, NW, MA, MS), pp. 1089–1096.
ICSM-2005-MarinMD: A Classification of Crosscutting Concerns (MM, LM, AvD), pp. 673–676.
SCAM-2005-PowerH #java #named #source code: Declassification: Transforming Java Programs to Remove Intermediate Classes (BP, GWH), pp. 183–192.
ICALP-2005-BraekenBNP #encryption: Classification of Boolean Functions of 6 Variables or Less with Respect to Some Cryptographic Properties (AB, YLB, SN, BP), pp. 324–334.
DiGRA-2005-ElverdamA #analysis #design #game studies: Game Classification as Game Design: Construction Through Critical Analysis (CE, EA).
ICEIS-v2-2005-NilssonFX #using: Clinical Decision Support by Time Series Classification Using Wavelets (MN, PF, NX), pp. 169–175.
ICEIS-v2-2005-Ruta #multi: Multidimensional Selection Model for Classification (DR), pp. 226–232.
ICEIS-v5-2005-DixitM #documentation #using: Electronic Document Classification Using Support Vector Machine — An Application for E-Learning (SD, LKM), pp. 191–198.
CIKM-2005-BoeseH #documentation #evolution #web: Effects of web document evolution on genre classification (ESB, AEH), pp. 632–639.
CIKM-2005-BotWCL #automation #concept #documentation #generative #using: Generating better concept hierarchies using automatic document classification (RSB, YfBW, XC, QL), pp. 281–282.
CIKM-2005-EsuliS #semantics: Determining the semantic orientation of terms through gloss classification (AE, FS), pp. 617–624.
CIKM-2005-GhamrawiM #multi: Collective multi-label classification (NG, AM), pp. 195–200.
CIKM-2005-KanT #performance #using: Fast webpage classification using URL features (MYK, HONT), pp. 325–326.
CIKM-2005-WangNZ #semantics: A latent semantic classification model (MWW, JYN, XQZ), pp. 261–262.
CIKM-2005-ZhangCFFGCC #multi: Intelligent GP fusion from multiple sources for text classification (BZ, YC, WF, EAF, MAG, MC, PC), pp. 477–484.
ECIR-2005-AyacheQC #using #video: Video Shot Classification Using Lexical Context (SA, GQ, MC), pp. 549–551.
ECIR-2005-MartonWH #on the: On Compression-Based Text Classification (YM, NW, LH), pp. 300–314.
ECIR-2005-SiersdorferW #strict #using: Using Restrictive Classification and Meta Classification for Junk Elimination (SS, GW), pp. 287–299.
ICML-2005-BeygelzimerDHLZ #fault #reduction: Error limiting reductions between classification tasks (AB, VD, TPH, JL, BZ), pp. 49–56.
ICML-2005-EspositoS #comparison #monte carlo: Experimental comparison between bagging and Monte Carlo ensemble classification (RE, LS), pp. 209–216.
ICML-2005-GlocerET #feature model #online: Online feature selection for pixel classification (KAG, DE, JT), pp. 249–256.
ICML-2005-HillD #adaptation #problem: Adapting two-class support vector classification methods to many class problems (SIH, AD), pp. 313–320.
ICML-2005-JingPR #learning #naive bayes #network #performance: Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes (YJ, VP, JMR), pp. 369–376.
ICML-2005-Keerthi #effectiveness #feature model: Generalized LARS as an effective feature selection tool for text classification with SVMs (SSK), pp. 417–424.
ICML-2005-KhoussainovHK: Ensembles of biased classifiers (RK, AH, NK), pp. 425–432.
ICML-2005-LangfordZ #learning #performance: Relating reinforcement learning performance to classification performance (JL, BZ), pp. 473–480.
ICML-2005-LavioletteM #bound: PAC-Bayes risk bounds for sample-compressed Gibbs classifiers (FL, MM), pp. 481–488.
ICML-2005-LeiteB #performance #predict: Predicting relative performance of classifiers from samples (RL, PB), pp. 497–503.
ICML-2005-MannorPR: The cross entropy method for classification (SM, DP, RYR), pp. 561–568.
ICML-2005-PernkopfB #generative #learning #network #parametricity: Discriminative versus generative parameter and structure learning of Bayesian network classifiers (FP, JAB), pp. 657–664.
ICML-2005-Pietraszek #analysis #optimisation #using: Optimizing abstaining classifiers using ROC analysis (TP), pp. 665–672.
ICML-2005-RamakrishnanCKB #approximate: A model for handling approximate, noisy or incomplete labeling in text classification (GR, KPC, RK, PB), pp. 681–688.
ICML-2005-RousuSSS #learning #modelling #multi: Learning hierarchical multi-category text classification models (JR, CS, SS, JST), pp. 744–751.
ICML-2005-SonnenburgRS #scalability #sequence: Large scale genomic sequence SVM classifiers (SS, GR, BS), pp. 848–855.
ICML-2005-VeeramachaneniSA #documentation: Hierarchical Dirichlet model for document classification (SV, DS, PA), pp. 928–935.
ICML-2005-WangS #kernel: New kernels for protein structural motif discovery and function classification (CW, SDS), pp. 940–947.
ICML-2005-WilliamsLXC #using: Incomplete-data classification using logistic regression (DW, XL, YX, LC), pp. 972–979.
ICML-2005-WuMR #detection #linear #symmetry: Linear Asymmetric Classifier for cascade detectors (JW, MDM, JMR), pp. 988–995.
ICML-2005-WuSB #scalability: Building Sparse Large Margin Classifiers (MW, BS, GHB), pp. 996–1003.
KDD-2005-Aggarwal #algorithm #towards: Towards exploratory test instance specific algorithms for high dimensional classification (CCA), pp. 526–531.
KDD-2005-ChenH #analysis #image #network: A Bayesian network classifier with inverse tree structure for voxelwise magnetic resonance image analysis (RC, EH), pp. 4–12.
KDD-2005-Kolcz #naive bayes: Local sparsity control for naive Bayes with extreme misclassification costs (AK), pp. 128–137.
KDD-2005-ManeSH #independence #using: Estimating missed actual positives using independent classifiers (SM, JS, SYH), pp. 648–653.
KDD-2005-Sandler #linear #on the #programming #using: On the use of linear programming for unsupervised text classification (MS), pp. 256–264.
KDD-2005-ZhangWZ #privacy: A new scheme on privacy-preserving data classification (NZ, SW, WZ), pp. 374–383.
MLDM-2005-Bak #linear #multi: A New Multidimensional Feature Transformation for Linear Classifiers and Its Applications (EB), pp. 275–284.
MLDM-2005-GuptaKB #concept analysis #incremental #using: Incremental Classification Rules Based on Association Rules Using Formal Concept Analysis (AG, NK, VB), pp. 11–20.
MLDM-2005-HayashiMS: Embedding Time Series Data for Classification (AH, YM, NS), pp. 356–365.
MLDM-2005-KoK #on the: On ECOC as Binary Ensemble Classifiers (JK, EK), pp. 1–10.
MLDM-2005-LeHS #ambiguity #approach #reasoning #word: An Evidential Reasoning Approach to Weighted Combination of Classifiers for Word Sense Disambiguation (CAL, VNH, AS), pp. 516–525.
MLDM-2005-MakrehchiK #using: Text Classification Using Small Number of Features (MM, MSK), pp. 580–589.
MLDM-2005-SzepannekLW #comprehension: Understanding Patterns with Different Subspace Classification (GS, KL, CW), pp. 110–119.
MLDM-2005-TakigawaKN #combinator #product line #set #subclass: The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets (IT, MK, AN), pp. 90–99.
SEKE-2005-ChiangTK #multi #performance #using: Fast Class Rendering Using Multiresolution Classification in Discrete Cosine Transform Domain (TWC, TT, LJK), pp. 689–694.
SIGIR-2005-BeitzelJFGLCK #automation #query #using #web: Automatic web query classification using labeled and unlabeled training data (SMB, ECJ, OF, DAG, DDL, AC, AK), pp. 581–582.
SIGIR-2005-CarvalhoC #email #on the #speech: On the collective classification of email “speech acts” (VRdC, WWC), pp. 345–352.
SIGIR-2005-MaL #automation #documentation #paradigm #semantics: A phonotactic-semantic paradigm for automatic spoken document classification (BM, HL), pp. 369–376.
SIGIR-2005-OlssonOH: Cross-language text classification (JSO, DWO, JH), pp. 645–646.
SIGIR-2005-TanCWXGG #using: Using dragpushing to refine centroid text classifiers (ST, XC, BW, HX, MG, YG), pp. 653–654.
SIGIR-2005-ZhangCFFGCC: Intelligent fusion of structural and citation-based evidence for text classification (BZ, YC, WF, EAF, MAG, MC, PC), pp. 667–668.
SIGIR-2005-ZhangCL #kernel #multi: Text classification with kernels on the multinomial manifold (DZ, XC, WSL), pp. 266–273.
SIGIR-2005-ZhuJXG #multi #using: Multi-labelled classification using maximum entropy method (SZ, XJ, WX, YG), pp. 274–281.
ECOOP-2005-PachecoE #automation #generative #named #testing: Eclat: Automatic Generation and Classification of Test Inputs (CP, MDE), pp. 504–527.
ESEC-FSE-2005-HaranKOPS #execution: Applying classification techniques to remotely-collected program execution data (MH, AFK, AO, AAP, APS), pp. 146–155.
ICSE-2005-HostWT #experience: Experimental context classification: incentives and experience of subjects (MH, CW, TT), pp. 470–478.
SAC-2005-DalkilicS05a #design #implementation #named: Circle: design and implementation of a classifier based on circuit minimization (MMD, AS), pp. 547–548.
SAC-2005-DongH #clustering #parametricity: Text classification based on data partitioning and parameter varying ensembles (YSD, KSH), pp. 1044–1048.
SAC-2005-FradkinK #learning: Methods for learning classifier combinations: no clear winner (DF, PBK), pp. 1038–1043.
SAC-2005-HacheyG #modelling #sequence #summary: Sequence modelling for sentence classification in a legal summarisation system (BH, CG), pp. 292–296.
SAC-2005-LiY #predict #recursion #using: Using recursive classification to discover predictive features (FL, YY), pp. 1054–1058.
SAC-2005-OcaGA #algorithm #clustering #network: An hybridization of an ant-based clustering algorithm with growing neural gas networks for classification tasks (MAMdO, LG, JLA), pp. 9–13.
SAC-2005-QianZQ #image: Spatial contextual noise removal for post classification smoothing of remotely sensed images (YQ, KZ, FQ), pp. 524–528.
CGO-2005-StephensonA #predict #using: Predicting Unroll Factors Using Supervised Classification (MS, SPA), pp. 123–134.
DAC-2005-McGeeN #design #framework #pipes and filters: A lattice-based framework for the classification and design of asynchronous pipelines (PBM, SMN), pp. 491–496.
HPCA-2005-LauSC #predict: Transition Phase Classification and Prediction (JL, SS, BC), pp. 278–289.
ESOP-2005-GiacobazziM #abstract interpretation #modelling: Adjoining Declassification and Attack Models by Abstract Interpretation (RG, IM), pp. 295–310.
ESOP-2005-TseZ #design: A Design for a Security-Typed Language with Certificate-Based Declassification (ST, SZ), pp. 279–294.
DRR-2004-NagyJKLLMS #parametricity: A nonparametric classifier for unsegmented text (GN, AJ, MSK, YL, DPL, SKM, SCS), pp. 102–108.
HT-2004-StottsF #hypermedia: Language-theoretic classification of hypermedia paths (PDS, RF), pp. 40–41.
JCDL-2004-ChenH #library #multi: Multi-modal classification in digital news libraries (MyC, AGH), pp. 212–213.
JCDL-2004-FanLXW #concept #nondeterminism #semantics #set #video: Semantic video classification and feature subset selection under context and concept uncertainty (JF, HL, JX, LW), pp. 192–201.
VLDB-2004-Fan #concept #data type #named: StreamMiner: A Classifier Ensemble-based Engine to Mine Concept-drifting Data Streams (WF), pp. 1257–1260.
ICEIS-v2-2004-KotsiantisP #hybrid #using: A Hybrid Decision Support Tool — Using Ensemble of Classifiers (SBK, PEP), pp. 448–456.
ICEIS-v2-2004-YounesTAR #image: Image Classification According to the Dominant Colour (AAY, IT, HA, YR), pp. 505–510.
ICEIS-v4-2004-MazhelisP #detection: Combining One-Class Classifiers for Mobile-User Substitution Detection (OM, SP), pp. 130–137.
CIKM-2004-SiersdorferSW #documentation #parametricity: Goal-oriented methods and meta methods for document classification and their parameter tuning (SS, SS, GW), pp. 59–68.
CIKM-2004-Zhang #information management: Weakly-supervised relation classification for information extraction (ZZ), pp. 581–588.
CIKM-2004-ZhangGFCFCC: Combining structural and citation-based evidence for text classification (BZ, MAG, WF, YC, EAF, PC, MC), pp. 162–163.
ECIR-2004-MoschittiB: Complex Linguistic Features for Text Classification: A Comprehensive Study (AM, RB), pp. 181–196.
ICML-2004-AltunHS #process #sequence: Gaussian process classification for segmenting and annotating sequences (YA, TH, AJS).
ICML-2004-BohteBG #parametricity #polynomial: Nonparametric classification with polynomial MPMC cascades (SMB, MB, GZG).
ICML-2004-Bouckaert #learning: Estimating replicability of classifier learning experiments (RRB).
ICML-2004-DekelKS #scalability: Large margin hierarchical classification (OD, JK, YS).
ICML-2004-EspositoS #analysis #monte carlo: A Monte Carlo analysis of ensemble classification (RE, LS).
ICML-2004-FerriFH: Delegating classifiers (CF, PAF, JHO).
ICML-2004-Forman #feature model #multi: A pitfall and solution in multi-class feature selection for text classification (GF).
ICML-2004-GrossmanD #learning #network: Learning Bayesian network classifiers by maximizing conditional likelihood (DG, PMD).
ICML-2004-HuangYKL #learning #scalability: Learning large margin classifiers locally and globally (KH, HY, IK, MRL).
ICML-2004-KoppelS #problem #verification: Authorship verification as a one-class classification problem (MK, JS).
ICML-2004-LebanonL #multi: Hyperplane margin classifiers on the multinomial manifold (GL, JDL).
ICML-2004-NguyenWJ #detection #distributed #kernel #using: Decentralized detection and classification using kernel methods (XN, MJW, MIJ).
ICML-2004-Zadrozny #bias #learning: Learning and evaluating classifiers under sample selection bias (BZ).
ICPR-v1-2004-ChengLLC #component #independence #kernel #using: Texture Classification Using Kernel Independent Component Analysi (JC, QL, HL, YWC), pp. 620–623.
ICPR-v1-2004-DmitryD #algorithm #effectiveness: Data Dependent Classifier Fusion for Construction of Stable Effective Algorithms (DV, DK), pp. 144–147.
ICPR-v1-2004-DuinPT #problem: The Characterization of Classification Problems by Classifier Disagreements (RPWD, EP, DMJT), pp. 140–143.
ICPR-v1-2004-GarainCG #multi #recognition: A Multiple-Classifier System for Recognition of Printed Mathematical Symbols (UG, BBC, RPG), pp. 380–383.
ICPR-v1-2004-GllavataEF #detection #image: Text Detection in Images Based on Unsupervised Classification of High-Frequency Wavelet Coefficients (JG, RE, BF), pp. 425–428.
ICPR-v1-2004-GocciaSD #fuzzy #learning #recognition: Learning Optimal Classifier Through Fuzzy Recognition Rate Maximization (MG, CS, SGD), pp. 204–207.
ICPR-v1-2004-HeLZZ #image #web: W-Boost and Its Application to Web Image Classification (JH, ML, HZ, CZ), pp. 148–151.
ICPR-v1-2004-Horikawa #comparison #invariant #kernel: Comparison of Support Vector Machines with Autocorrelation Kernels for Invariant Texture Classification (YH), pp. 660–663.
ICPR-v1-2004-Jager: Informational Classifier Fusion (SJ), pp. 216–219.
ICPR-v1-2004-KangD #approximate #bound #fault: Product Approximation by Minimizing the Upper Bound of Bayes Error Rate for Bayesian Combination of Classifiers (HJK, DSD), pp. 252–255.
ICPR-v1-2004-KolschKNP #image: Enhancements for Local Feature Based Image Classification (TK, DK, HN, RP), pp. 248–251.
ICPR-v1-2004-LeydierBE #adaptation #image #segmentation: Serialized Unsupervised Classifier for Adaptative Color Image Segmentation: Application to Digitized Ancient Manuscripts (YL, FLB, HE), pp. 494–497.
ICPR-v1-2004-LiS #design: SVM-Based Classifier Design with Controlled Confidence (ML, IKS), pp. 164–167.
ICPR-v1-2004-LiuM #recognition #string: Handwritten Numeral String Recognition: Character-Level vs. String-Level Classifier Training (CLL, KM), pp. 405–408.
ICPR-v1-2004-Manley-CookeR #fuzzy: A Modified Fuzzy Inference System for Pattern Classification (PMC, MR), pp. 256–259.
ICPR-v1-2004-MansillaH #on the: On Classifier Domains of Competence (EBiM, TKH), pp. 136–139.
ICPR-v1-2004-MilgramSC #modelling: Two-Stage Classification System combining Model-Based and Discriminative Approaches (JM, RS, MC), pp. 152–155.
ICPR-v1-2004-ToselliJV #recognition: Spontaneous Handwriting Recognition and Classification (AHT, AJ, EV), pp. 433–436.
ICPR-v1-2004-VaswaniC #analysis #component #null #probability: Classification Probability Analysis of Principal Component Null Space Analysis (NV, RC), pp. 240–243.
ICPR-v1-2004-WithagenSG #probability: Probabilistic Classification Between Foreground Objects and Background (PJW, KS, FCAG), pp. 31–34.
ICPR-v1-2004-XuC #statistics: Statistical Landscape Features for Texture Classification (CLX, YQC), pp. 676–679.
ICPR-v1-2004-YiKZ #learning: Classifier Combination based on Active Learning (XY, ZK, CZ), pp. 184–187.
ICPR-v1-2004-ZhangP: SVM vs Regularized Least Squares Classification (PZ, JP), pp. 176–179.
ICPR-v1-2004-ZouariHLA #performance #simulation: Simulating Classifier Ensembles of Fixed Diversity for Studying Plurality Voting Performance (HZ, LH, YL, AMA), pp. 232–235.
ICPR-v2-2004-BrownCA #performance #set: Efficient Calculation of the Complete Optimal Classification Set (MB, NC, SA), pp. 307–310.
ICPR-v2-2004-CaoK #online: Online Structure Based Chinese Character Pre-Classification (HC, ACK), pp. 395–398.
ICPR-v2-2004-DeselaersKN #evaluation #fault #image #retrieval: Classification Error Rate for Quantitative Evaluation of Content-based Image Retrieval Systems (TD, DK, HN), pp. 505–508.
ICPR-v2-2004-FarmerJ #approach #image #segmentation: A Wrapper-Based Approach to Image Segmentation and Classification (MEF, AKJ), pp. 106–109.
ICPR-v2-2004-HuR #clustering #probability #using: Probability Table Compression Using Distributional Clustering for Scanning N-Tuple Classifiers (JH, ER), pp. 533–536.
ICPR-v2-2004-IurgelR #documentation #probability #using: Spoken Document Classification with SVMs Using Linguistic Unit Weighting and Probabilistic Couplers (UI, GR), pp. 667–670.
ICPR-v2-2004-KaneS #image #learning #network: Bayesian Network Structure Learning and Inference in Indoor vs. Outdoor Image Classification (MJK, AES), pp. 479–482.
ICPR-v2-2004-LeungNL: ICA-FX Features for Classification of Singing Voice and Instrumental Sound (TWL, CWN, RWHL), pp. 367–370.
ICPR-v2-2004-LillholmP: Jet Based Feature Classification (ML, KSP), pp. 787–790.
ICPR-v2-2004-MaD #adaptation #using #word: Adaptive Word Style Classification Using a Gaussian Mixture Model (HM, DSD), pp. 606–609.
ICPR-v2-2004-MozaffarifK #comparison #recognition #using: Feature Comparison between Fractal Codes and Wavelet Transform in Handwritten Alphanumeric Recognition Using SVM Classifier (SM, KF, HRK), pp. 331–334.
ICPR-v2-2004-PranckevicieneBS #identification: Consensus-Based Identification of Spectral Signatures for Classification of High-Dimensional Biomedical Spectra (EP, RB, RLS), pp. 319–322.
ICPR-v2-2004-Rodriguez-DamianCFS #using: Pollen Classification using Brightness-Based and Shape-Based Descriptors (MRD, EC, AF, PdSO), pp. 212–215.
ICPR-v2-2004-RubeAK #invariant #multi: Coarse-to-Fine Multiscale Affine Invariant Shape Matching and Classification (IER, MA, MK), pp. 163–166.
ICPR-v2-2004-TahirBKA #feature model #using: Feature Selection using Tabu Search for Improving the Classification Rate of Prostate Needle Biopsies (MAT, AB, FK, AA), pp. 335–338.
ICPR-v2-2004-VijayaMS #clustering #performance #sequence: An Efficient Technique for Protein Sequence Clustering and Classification (PAV, MNM, DKS), pp. 447–450.
ICPR-v2-2004-WashizawaY #kernel #pattern matching #pattern recognition #recognition: Kernel Sample Space Projection Classifier for Pattern Recognition (YW, YY), pp. 435–438.
ICPR-v2-2004-XuGSRTW: High Accuracy Classification of EEG Signal (WX, CG, CES, SR, MT, JW), pp. 391–394.
ICPR-v2-2004-YamaguchiM #image: Character Extraction from Natural Scene Images by Hierarchical Classifiers (TY, MM), pp. 687–690.
ICPR-v2-2004-ZhangHHZ #kernel #visual notation: Kernel Autoassociator with Applications to Visual Classification (HZ, WH, ZH, BZ), pp. 443–446.
ICPR-v3-2004-ArchambeauBPVT #parametricity: Supervised Nonparametric Information Theoretic Classification (CA, TB, VP, MV, JPT), pp. 414–417.
ICPR-v3-2004-DEliaMMPST #clustering #detection #segmentation: Detection of Microcalcifications Clusters in Mammograms through TS-MRF Segmentation and SVM-based Classification (CD, CM, MM, GP, GS, FT), pp. 742–745.
ICPR-v3-2004-ForestiMS #automation: Event Classification for Automatic Visual-based Surveillance of Parking Lots (GLF, CM, LS), pp. 314–317.
ICPR-v3-2004-GutkinK #representation #speech: Structural Representation of Speech for Phonetic Classification (AG, SK), pp. 438–441.
ICPR-v3-2004-HolmstromH #estimation: Application of Semiparametric Density Estimation to Classification (LH, FH), pp. 371–374.
ICPR-v3-2004-JainH #component #gender #independence: Integrating Independent Components and Support Vector Machines for Gender Classification (AJ, JH), pp. 558–561.
ICPR-v3-2004-KatoW #algorithm #nearest neighbour #performance: Direct Condensing: An Efficient Voronoi Condensing Algorithm for Nearest Neighbor Classifiers (TK, TW), pp. 474–477.
ICPR-v3-2004-KuhlKWK #using: Training of Classifiers Using Virtual Samples Only (AK, LK, CW, UK), pp. 418–421.
ICPR-v3-2004-LiCKG #detection #image: Detecting Abnormal Regions in Colonoscopic Images by Patch-based Classifier Ensemble (PL, KLC, SMK, YG), pp. 774–777.
ICPR-v3-2004-LiewWY #sequence #statistics: Selection of Statistical Features Based on Mutual Information for Classification of Human Coding and Non-coding DNA Sequences (AWCL, YW, HY), pp. 766–769.
ICPR-v3-2004-PozdnoukhovB #image #invariant #kernel: Tangent Vector Kernels for Invariant Image Classification with SVMs (AP, SB), pp. 486–489.
ICPR-v3-2004-RahtuH #multi: Object Classification with Multi-Scale Autoconvolution (ER, JH), pp. 37–40.
ICPR-v3-2004-ReiterR #multi #programming #segmentation #using: Segmentation and Classification of Meeting Events using Multiple Classifier Fusion and Dynamic Programming (SR, GR), pp. 434–437.
ICPR-v3-2004-ShiNGY #learning: Critical Vector Learning to Construct RBF Classifiers (DS, GSN, JG, DSY), pp. 359–362.
ICPR-v3-2004-SprevakAW #assessment: A Non-Random Data Sampling Method for Classification Model Assessment (DS, FA, HW), pp. 406–409.
ICPR-v3-2004-TaxM: A Consistency-Based Model Selection for One-Class Classification (DMJT, KRM), pp. 363–366.
ICPR-v3-2004-Windeatt #design: Diversity/Accuracy and Ensemble Classifier Design (TW), pp. 454–457.
ICPR-v3-2004-WuAH #image #retrieval: Facial Image Retrieval Based on Demographic Classification (BW, HA, CH), pp. 914–917.
ICPR-v3-2004-ZhouK04a: The Pattern Classification Based on the Nearest Feature Midpoints (ZZ, CKK), pp. 446–449.
ICPR-v4-2004-BoutellL04a #image #metadata: Photo Classification by Integrating Image Content and Camera Metadata (MRB, JL), pp. 901–904.
ICPR-v4-2004-Cardenas #learning #multi #prototype #string: A Learning Model for Multiple-Prototype Classification of Strings (RAM), pp. 420–423.
ICPR-v4-2004-GorgevikC #performance #recognition: An Efficient Three-Stage Classifier for Handwritten Digit Recognition (DG, DC), pp. 507–510.
ICPR-v4-2004-HakeemS #framework #ontology #taxonomy: Ontology and Taxonomy Collaborated Framework for Meeting Classification (AH, MS), pp. 219–222.
ICPR-v4-2004-LimJ #image: Cascading Classifiers for Consumer Image Indexing (JHL, JSJ), pp. 897–900.
ICPR-v4-2004-LiuWLT #recognition: Nearest Intra-Class Space Classifier for Face Recognition (WL, YW, SZL, TT), pp. 495–498.
ICPR-v4-2004-LiuWP #composition #empirical: Texture Classification Through Directional Empirical Mode Decomposition (ZL, HW, SP), pp. 803–806.
ICPR-v4-2004-Moreno-SecoMO #nearest neighbour #rule-based: A New Classification Rule based on Nearest Neighbour Search (FMS, LM, JO), pp. 408–411.
ICPR-v4-2004-MurinoBR #fault #statistics: Statistical Classification of Raw Textile Defects (VM, MB, IAR), pp. 311–314.
ICPR-v4-2004-NandedkarB #architecture #fuzzy #network: A Fuzzy Min-Max Neural Network Classifier with Compensatory Neuron Architecture (AVN, PKB), pp. 553–556.
ICPR-v4-2004-OuMF #multi #network #using: Multiclass Pattern Classification Using Neural Networks (GO, YLM, LAF), pp. 585–588.
ICPR-v4-2004-ShapiroG #multi #recognition #segmentation: Multinational License Plate Recognition System: Segmentation and Classification (VS, GG), pp. 352–355.
ICPR-v4-2004-ShettyR #detection #modelling: An Undecimated Wavelet Transform Based Denoising, PPCA Based Pulse Modeling and Detection-Classification of PD Signals (PKS, TSR), pp. 873–876.
ICPR-v4-2004-UekiKIKISKK #gender #image: A Method of Gender Classification by Integrating Facial, Hairstyle, and Clothing Images (KU, HK, SI, KK, NS, JK, TK), pp. 446–449.
ICPR-v4-2004-ViswanathMB #nearest neighbour #pattern matching #pattern recognition #performance #recognition #synthesis: A Pattern Synthesis Technique with an Efficient Nearest Neighbor Classifier for Binary Pattern Recognition (PV, MNM, SB), pp. 416–419.
KDD-2004-AggarwalHWY #data type #on the: On demand classification of data streams (CCA, JH, JW, PSY), pp. 503–508.
KDD-2004-AksoyKTM #image #interactive #mining: Interactive training of advanced classifiers for mining remote sensing image archives (SA, KK, CT, GBM), pp. 773–782.
KDD-2004-DalviDMSV: Adversarial classification (NND, PMD, M, SKS, DV), pp. 99–108.
KDD-2004-JensenNG #relational #why: Why collective inference improves relational classification (DJ, JN, BG), pp. 593–598.
KDD-2004-LiuYM #algorithm #parametricity #performance: The IOC algorithm: efficient many-class non-parametric classification for high-dimensional data (TL, KY, AWM), pp. 629–634.
KDD-2004-PavlovBDKP #clustering #documentation #multi #naive bayes #preprocessor: Document preprocessing for naive Bayes classification and clustering with mixture of multinomials (DP, RB, BD, SK, JP), pp. 829–834.
KR-2004-GrootTH #analysis #approximate #case study #problem #towards: Towards a Structured Analysis of Approximate Problem Solving: A Case Study in Classification (PG, AtT, FvH), pp. 399–406.
KR-2004-Pirri: Indoor Environment Classification and Perceptual Matching (FP), pp. 73–84.
SEKE-2004-KhoshgoftaarJ #case study #quality: Noise Elimination with Ensemble-Classifier Filtering: A Case-Study in Software Quality Engineerin (TMK, VHJ), pp. 226–231.
SIGIR-2004-AeryC #email #named: eMailSift: mining-based approaches to email classification (MA, SC), pp. 580–581.
SIGIR-2004-FanL #semantics #video: Semantic video classification by integrating unlabeled samples for classifier training (JF, HL), pp. 592–593.
SIGIR-2004-KumaranA #detection: Text classification and named entities for new event detection (GK, JA), pp. 297–304.
SIGIR-2004-MladenicBGM #feature model #interactive #linear #modelling #using: Feature selection using linear classifier weights: interaction with classification models (DM, JB, MG, NMF), pp. 234–241.
SIGIR-2004-ShenCYZZLM #summary: Web-page classification through summarization (DS, ZC, QY, HJZ, BZ, YL, WYM), pp. 242–249.
SIGIR-2004-YangC #effectiveness #web: Effectiveness of web page classification on finding list answers (HY, TSC), pp. 522–523.
SIGIR-2004-Zhang #adaptation #using: Using bayesian priors to combine classifiers for adaptive filtering (YZ0), pp. 345–352.
UML-2004-JiangSZMMM #metamodelling #on the #uml: On the Classification of UML’s Meta Model Extension Mechanism (YJ, WS, LZ, ZM, XM, HM), pp. 54–68.
FSE-2004-RinardSB #analysis #aspect-oriented #source code: A classification system and analysis for aspect-oriented programs (MCR, AS, SB), pp. 147–158.
SAC-2004-BaralisCG #on the: On support thresholds in associative classification (EB, SC, PG), pp. 553–558.
SAC-2004-BeneventanoM #framework: A framework for the classification and the reclassification of electronic catalogs (DB, SM), pp. 784–788.
SAC-2004-DamianiDG #multi #thread: Re-classification and multi-threading: Fickle_MT (FD, MDC, PG), pp. 1297–1304.
SAC-2004-EggermontKK #clustering #programming #search-based: Genetic Programming for data classification: partitioning the search space (JE, JNK, WAK), pp. 1001–1005.
SAC-2004-ZhouL #network: Regularized B-spline network and its application to heart arrhythmia classification (JZ, LL), pp. 291–295.
SAC-PL-J-2004-DamianiDG #multi #on the #thread: On Re-classification and Multi-threading (FD, MDC, PG), pp. 5–30.
OSDI-2004-GniadyBH: Program-Counter-Based Pattern Classification in Buffer Caching (CG, ARB, YCH), pp. 395–408.
ESOP-2004-CalcagnoMT: ML-Like Inference for Classifiers (CC, EM, WT), pp. 79–93.
IJCAR-2004-ColtonMSM #algebra #automation #finite #generative #theorem: Automatic Generation of Classification Theorems for Finite Algebras (SC, AM, VS, RLM), pp. 400–414.
DocEng-2003-DenoyerVGBB #documentation #multi: Structured multimedia document classification (LD, JNV, PG, SB, SB), pp. 153–160.
DocEng-2003-ZuOWK #automation: Accuracy improvement of automatic text classification based on feature transformation (GZ, WO, TW, FK), pp. 118–120.
DRR-2003-Summers #documentation #image #problem: Document image improvment for OCR as a classification problem (KMS), pp. 73–83.
ECDL-2003-FerilliEBM #automation #induction: Automatic Induction of Rules for Classification and Interpretation of Cultural Heritage Material (SF, FE, TMAB, NDM), pp. 152–163.
ICDAR-2003-BaldiMS #set #using: Using tree-grammars for training set expansion in page classification (SB, SM, GS), pp. 829–833.
ICDAR-2003-Biem #optimisation: A Model Selection Criterion for Classification: Application to HMM Topology Optimization (AB), pp. 104–108.
ICDAR-2003-EglinB #documentation #layout #query #similarity #visual notation: Document page similarity based on layout visual saliency: Application to query by example and document classification (VE, SB), pp. 1208–1212.
ICDAR-2003-FutrelleSCG #analysis #diagrams #documentation #layout: Extraction, layout analysis and classification of diagrams in PDF documents (RPF, MS, CC, AEG), pp. 1007–1014.
ICDAR-2003-GocciaBSD #feature model #optimisation #recognition: Recognition of Container Code Characters through Gray-Level Feature Extraction and Gradient-Based Classifier Optimization (MG, MB, CS, SGD), p. 973–?.
ICDAR-2003-GuestCFP #analysis #automation #geometry #sequence #using: Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis (RMG, SC, MCF, JMP), pp. 990–994.
ICDAR-2003-HamamuraMI #multi: A Multiclass Classification Method Based on Multiple Pairwise Classifiers (TH, HM, BI), pp. 809–813.
ICDAR-2003-HaoLS #evaluation: Confidence Evaluation for Combining Diverse Classifiers (HH, CLL, HS), pp. 760–764.
ICDAR-2003-HaoLS03a #algorithm #comparison #search-based #set: Comparison of Genetic Algorithm and Sequential Search Methods for Classifier Subset Selection (HH, CLL, HS), pp. 765–769.
ICDAR-2003-HoqueSF #approach #multi #performance #recognition: A New Chain-code Quantization Approach Enabling High Performance Handwriting Recognition based on Multi-Classifier Schemes (SH, KS, MCF), pp. 834–838.
ICDAR-2003-KangD #dependence #higher-order #multi: Combining Multiple Classifiers based on Third-Order Dependency (HJK, DSD), pp. 21–25.
ICDAR-2003-KangD03a #evaluation #multi: Evaluation of the Information-Theoretic Construction of Multiple Classifier Systems (HJK, DSD), pp. 789–793.
ICDAR-2003-KimMO #algorithm #statistics #word: A Text Watermarking Algorithm based on Word Classification and Inter-word Space Statistics (YWK, KAM, ISO), pp. 775–779.
ICDAR-2003-LeeO #multi #problem: Binary Classification Trees for Multi-class Classification Problems (JSL, ISO), pp. 770–774.
ICDAR-2003-MaD #documentation #image #multi: Gabor Filter Based Multi-class Classifier for Scanned Document Images (HM, DSD), pp. 968–972.
ICDAR-2003-PrevostMMOM #modelling #recognition: Combining model-based and discriminative classifiers : application to handwritten character recognition (LP, CMS, AM, LO, MM), p. 31–?.
ICDAR-2003-RagotA #fuzzy #hybrid #modelling #online #recognition: A Generic Hybrid Classifier Based on Hierarchical Fuzzy Modeling: Experiments on On-Line Handwritten Character Recognition (NR, ÉA), pp. 963–967.
ICDAR-2003-SchenkerLBK #documentation #graph #using #web: Classification of Web Documents Using a Graph Model (AS, ML, HB, AK), pp. 240–244.
ICDAR-2003-StefanoCM #algorithm #reliability #search-based: Exploiting Reliability for Dynamic Selection of Classifiers by Means of Genetic Algorithms (CDS, ADC, AM), pp. 671–675.
ICDAR-2003-VelekN #online #performance #recognition #scalability #set: Enhancing Efficiency and Speed of an Off-line Classifier Employed for On-line Handwriting Recognition of a Large Character Set (OV, MN), pp. 784–788.
ICDAR-2003-YamaguchiNMMH #recognition: Digit Classification on Signboards for Telephone Number Recognition (TY, YN, MM, HM, TH), pp. 359–363.
ICDAR-2003-ZouariHLA #parallel: A New Classifier Simulator for Evaluating Parallel Combination Methods (HZ, LH, YL, AMA), pp. 26–30.
SIGMOD-2003-FaginKS #performance #rank #similarity: Efficient similarity search and classification via rank aggregation (RF, RK, DS), pp. 301–312.
ICSM-2003-Gustavsson #java #runtime: A Classification of Unanticipated Runtime Software Changes in Java (JG), pp. 4–12.
ICEIS-v2-2003-HassanienA #algorithm #image #performance #retrieval #set: An Efficient Classification and Image Retrieval Algorithm Based on Rough Set Theory (AEH, JMHA), pp. 457–460.
ICEIS-v2-2003-TungFB #information management: Knowledge Management and Data Classification in Pellucid (TTD, BF, IB), pp. 209–216.
ICEIS-v3-2003-ToffolonD03a #prototype: Software Prototyping Classification (CT, SD), pp. 266–271.
ICEIS-v4-2003-PlaisentOBM #internet #towards: Toward a Classification of Internet Scientific Conferences (MP, AO, PB, LM), pp. 473–476.
CIKM-2003-AdamiAS #documentation: Bootstrapping for hierarchical document classification (GA, PA, DS), pp. 295–302.
CIKM-2003-CaladoCMZRG #documentation #web: Combining link-based and content-based methods for web document classification (PC, MC, ESdM, NZ, BARN, MAG), pp. 394–401.
CIKM-2003-KaoQPW #information management: User assisted text classification and knowledge management (AK, LQ, SP, SW), pp. 524–527.
CIKM-2003-MacskassyH: Adding numbers to text classification (SAM, HH), pp. 240–246.
CIKM-2003-ShanahanR: Boosting support vector machines for text classification through parameter-free threshold relaxation (JGS, NR), pp. 247–254.
CIKM-2003-YuZH #documentation: Text classification from positive and unlabeled documents (HY, CZ, JH), pp. 232–239.
ECIR-2003-CeciM #documentation #html: Hierarchical Classification of HTML Documents with WebClassII (MC, DM), pp. 57–72.
ECIR-2003-FisherE: When Are Links Useful? Experiments in Text Classification (MF, RME), pp. 41–56.
ECIR-2003-Moschitti #case study #parametricity: A Study on Optimal Parameter Tuning for Rocchio Text Classifier (AM), pp. 420–435.
ECIR-2003-PengS #modelling #n-gram #naive bayes: Combining Naive Bayes and n-Gram Language Models for Text Classification (FP, DS), pp. 335–350.
ECIR-2003-XuYTXW #using: Representative Sampling for Text Classification Using Support Vector Machines (ZX, KY, VT, XX, JW), pp. 393–407.
ICML-2003-DeCosteM #approximate #incremental #kernel #performance: Fast Query-Optimized Kernel Machine Classification Via Incremental Approximate Nearest Support Vectors (DD, DM), pp. 115–122.
ICML-2003-Jaeger #concept #probability: Probabilistic Classifiers and the Concepts They Recognize (MJ), pp. 266–273.
ICML-2003-KlautauJO #comparison #kernel #modelling: Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers (AK, NJ, AO), pp. 353–360.
ICML-2003-KrishnapuramCJ #documentation: Classification of Text Documents Based on Minimum System Entropy (RK, KPC, SJ), pp. 384–391.
ICML-2003-LachicheF #multi #probability #using: Improving Accuracy and Cost of Two-class and Multi-class Probabilistic Classifiers Using ROC Curves (NL, PAF), pp. 416–423.
ICML-2003-LagoudakisP #learning: Reinforcement Learning as Classification: Leveraging Modern Classifiers (MGL, RP), pp. 424–431.
ICML-2003-LiWL #generative #keyword #probability #using: Text Classification Using Stochastic Keyword Generation (CL, JRW, HL), pp. 464–471.
ICML-2003-LiY #analysis #categorisation: A Loss Function Analysis for Classification Methods in Text Categorization (FL, YY), pp. 472–479.
ICML-2003-LuG: Link-based Classification (QL, LG), pp. 496–503.
ICML-2003-PorterEHT #order #scalability #statistics: Weighted Order Statistic Classifiers with Large Rank-Order Margin (RBP, DE, DRH, JT), pp. 600–607.
ICML-2003-RennieSTK #naive bayes: Tackling the Poor Assumptions of Naive Bayes Text Classifiers (JDR, LS, JT, DRK), pp. 616–623.
ICML-2003-RosipalTM #kernel #linear: Kernel PLS-SVC for Linear and Nonlinear Classification (RR, LJT, BM), pp. 640–647.
ICML-2003-YanDMW #approximate #optimisation #performance #statistics: Optimizing Classifier Performance via an Approximation to the Wilcoxon-Mann-Whitney Statistic (LY, RHD, MM, RHW), pp. 848–855.
KDD-2003-BhatnagarKN #mining: Mining high dimensional data for classifier knowledge (RB, GK, WN), pp. 481–486.
KDD-2003-WangFYH #concept #data type #mining #using: Mining concept-drifting data streams using ensemble classifiers (HW, WF, PSY, JH), pp. 226–235.
KDD-2003-ZakiA #effectiveness #named #xml: XRules: an effective structural classifier for XML data (MJZ, CCA), pp. 316–325.
MLDM-2003-BouguilaZV #image #novel: Novel Mixtures Based on the Dirichlet Distribution: Application to Data and Image Classification (NB, DZ, JV), pp. 172–181.
MLDM-2003-EstruchFHR: Simple Mimetic Classifiers (VE, CF, JHO, MJRQ), pp. 156–171.
MLDM-2003-KuhnertK #image #learning: A Learning Autonomous Driver System on the Basis of Image Classification and Evolutional Learning (KDK, MK), pp. 400–412.
MLDM-2003-MiteranBB #approximate #bound #image #realtime #segmentation #using: Classification Boundary Approximation by Using Combination of Training Steps for Real-Time Image Segmentation (JM, SB, EBB), pp. 141–155.
MLDM-2003-Scaringella #on the: On the Size of a Classification Tree (AS), pp. 65–72.
SIGIR-2003-Bennett #probability #symmetry #using: Using asymmetric distributions to improve text classifier probability estimates (PNB), pp. 111–118.
SIGIR-2003-HanMGZ #clustering #rule-based #word: Rule-based word clustering for text classification (HH, EM, CLG, HZ), pp. 445–446.
SIGIR-2003-KangK #documentation #query #retrieval #web: Query type classification for web document retrieval (IHK, GCK), pp. 64–71.
SIGIR-2003-KrovetzUG #source code: Classification of source code archives (RK, SU, CLG), pp. 425–426.
SIGIR-2003-LiOL #case study #comparative #music: A comparative study on content-based music genre classification (TL, MO, QL), pp. 282–289.
SIGIR-2003-TsaiMT #hybrid #image #network #using: Image classification using hybrid neural networks (CFT, KM, JT), pp. 431–432.
SIGIR-2003-YangZK #analysis #categorisation #scalability: A scalability analysis of classifiers in text categorization (YY, JZ, BK), pp. 96–103.
SIGIR-2003-ZhangL #using: Question classification using support vector machines (DZ, WSL), pp. 26–32.
SIGIR-2003-ZhangY #categorisation #linear #robust: Robustness of regularized linear classification methods in text categorization (JZ, YY), pp. 190–197.
POPL-2003-TahaN: Environment classifiers (WT, MFN), pp. 26–37.
SAC-2003-LiZLO #functional #learning #semistructured data: Gene Functional Classification by Semisupervised Learning from Heterogeneous Data (TL, SZ, QL, MO), pp. 78–82.
SAC-2003-NenkovaB #email: Email Classification for Contact Centers (AN, AB), pp. 789–792.
SAC-2003-WangBD #approach: A Density Based Approach to Classification (HW, DAB, ID), pp. 470–474.
SAC-2003-WombacherMR #ad hoc #modelling #multi #workflow: Classification of Ad hoc Multi-lateral Collaborations Based on Local Workflow Models (AW, BM, TR), pp. 1185–1190.
SAC-2003-YangH #data flow #image #using: Image Texture Classification Using Datagrams and Characteristic Views (SY, CCH), pp. 22–26.
SAC-2003-YuNPC #on the #testing #using: On the Use of the Classification-Tree Method by Beginning Software Testers (YTY, SPN, PLP, TYC), pp. 1123–1127.
DATE-2003-CorsiMM #approach #pseudo #random testing #testing: An Approach to the Classification of Mixed-Signal Circuits in a Pseudorandom Testing Scheme (FC, CM, GM), pp. 11178–11179.
ECDL-2002-GreenbergBJDW #comprehension #education #library #student: Student Comprehension of Classification Applications in a Science Education Digital Library (JG, KAB, MLJ, ED, PW), pp. 560–567.
ECDL-2002-SunLN #keyword #personalisation: Personalized Classification for Keyword-Based Category Profiles (AS, EPL, WKN), pp. 61–74.
JCDL-2002-CuiHZ #approach #automation #information retrieval: An approach to automatic classification of text for information retrieval (HC, PBH, HZ), pp. 96–97.
JCDL-2002-TudhopeBBC: Compound descriptors in context: a matching function for classifications and thesauri (DT, CB, DB, DC), pp. 84–93.
VLDB-2002-ChakrabartiRS #linear #multi #performance: Fast and Accurate Text Classification via Multiple Linear Discriminant Projections (SC, SR, MVS), pp. 658–669.
FME-2002-HendersonP #communication #verification: The Formal Classification and Verification of Simpson’s 4-Slot Asynchronous Communication Mechanism (NH, SP), pp. 350–369.
ICEIS-2002-SantosNASR #data mining #database #learning #mining #using: Augmented Data Mining over Clinical Databases Using Learning Classifier Systems (MFS, JN, AA, ÁMS, FR), pp. 512–516.
ICEIS-2002-Veryha #database #fuzzy #implementation #query #relational #using: Implementation of Fuzzy Classification Query Language in Relational Databases Using Stored Procedures (YV), pp. 195–202.
CIKM-2002-DeshpandeK #using: Using conjunction of attribute values for classification (MD, GK), pp. 356–364.
CIKM-2002-LiuH #identification #music: A singer identification technique for content-based classification of MP3 music objects (CCL, CSH), pp. 438–445.
CIKM-2002-LiuYC #bias #induction: Boosting to correct inductive bias in text classification (YL, YY, JGC), pp. 348–355.
CIKM-2002-RogatiY #feature model: High-performing feature selection for text classification (MR, YY), pp. 659–661.
CIKM-2002-StehlingNF #approach #image #performance #retrieval: A compact and efficient image retrieval approach based on border/interior pixel classification (ROS, MAN, AXF), pp. 102–109.
ECIR-2002-FinnKS #information management: Genre Classification and Domain Transfer for Information Filtering (AF, NK, BS), pp. 353–362.
ICML-2002-DashC #naive bayes: Exact model averaging with naive Bayesian classifiers (DD, GFC), pp. 91–98.
ICML-2002-DeCoste #distance #geometry #kernel #performance: Anytime Interval-Valued Outputs for Kernel Machines: Fast Support Vector Machine Classification via Distance Geometry (DD), pp. 99–106.
ICML-2002-DzeroskiZ: Is Combining Classifiers Better than Selecting the Best One (SD, BZ), pp. 123–130.
ICML-2002-Ho: Classification Value Grouping (CKMH), pp. 251–258.
ICML-2002-LiuLYL #documentation: Partially Supervised Classification of Text Documents (BL, WSL, PSY, XL), pp. 387–394.
ICML-2002-RaskuttiFK #clustering #parametricity #using: Using Unlabelled Data for Text Classification through Addition of Cluster Parameters (BR, HLF, AK), pp. 514–521.
ICML-2002-ThamDR #learning #markov #monte carlo #using: Sparse Bayesian Learning for Regression and Classification using Markov Chain Monte Carlo (SST, AD, KR), pp. 634–641.
ICML-2002-Ting #evaluation #using: Issues in Classifier Evaluation using Optimal Cost Curves (KMT), pp. 642–649.
ICML-2002-YangW: Non-Disjoint Discretization for Naive-Bayes Classifiers (YY, GIW), pp. 666–673.
ICPR-v1-2002-ArlandisPC #metric: Rejection Strategies and Confidence Measures for a k- NN Classifier in an OCR Task (JA, JCPC, JCP), pp. 576–579.
ICPR-v1-2002-Baggenstoss: The Chain-Rule Processor: Optimal Classification Through Signal Processing (PMB), pp. 230–234.
ICPR-v1-2002-ClaudeWPB #image #network: Contour Features for Colposcopic Image Classification by Artificial Neural Networks (IC, RW, PP, JCB), pp. 771–774.
ICPR-v1-2002-DuchesneBBC #image #on the #using: On the Classification of Temporal Lobe Epilepsy Using MR Image Appearance (SD, NB, AB, DLC), pp. 520–523.
ICPR-v1-2002-KampelS #automation #segmentation: Automated Segmentation of Archaeological Profiles or Classification (MK, RS), pp. 57–60.
ICPR-v1-2002-LiuS #recognition #representation: A Spectral Representation for Appearance-Based Classification and Recognition (XL, AS), pp. 37–40.
ICPR-v1-2002-SebeLCGH #naive bayes #recognition #using: Emotion Recognition Using a Cauchy Naive Bayes Classifier (NS, MSL, IC, AG, TSH), p. 17–?.
ICPR-v1-2002-Souafi-BensafiPLE #documentation #network: Bayesian Networks Classifiers Applied to Documents (SSB, MP, FL, HE), p. 483–?.
ICPR-v1-2002-Torkkola #documentation: Discriminative Features for Document Classification (KT), pp. 472–475.
ICPR-v1-2002-ZhangD #fault #recognition: Minimum Classification Error Training for Handwritten Character Recognition (RZ, XD), pp. 580–583.
ICPR-v1-2002-ZhuY #documentation: A New Textual/Non-Textual Classifier for Document Skew Correction (XZ, XY), pp. 480–482.
ICPR-v2-2002-AksoyH #framework #image #retrieval: A Classification Framework for Content-Based Image Retrieval (SA, RMH), pp. 503–506.
ICPR-v2-2002-AltyncayD #multi #normalisation #problem #question #why: Why Does Output Normalization Create Problems in Multiple Classifier Systems? (HA, MD), pp. 775–778.
ICPR-v2-2002-BalthasarP #performance: Fast Projection Plane Classifier (DB, LP), pp. 200–203.
ICPR-v2-2002-BarataP #clustering #modelling #set #using: Improving Classification Rates by Modelling the Clusters of Trainings Sets in Features Space Using Mathematical Morphology Operators (TB, PP), pp. 328–331.
ICPR-v2-2002-ChoCWS #adaptation #data type #image #learning #representation #robust: Robust Learning in Adaptive Processing of Data Structures for Tree Representation Based Image Classification (SYC, ZC, ZW, WCS), pp. 108–111.
ICPR-v2-2002-Duin #question: The Combining Classifier: To Train or Not to Train? (RPWD), pp. 765–770.
ICPR-v2-2002-ErcilB #polynomial #using: One Class Classification Using Implicit Polynomial Surface Fitting (AE, BB), pp. 152–155.
ICPR-v2-2002-FrantiX #using: Classification of Binary Vectors by Using ??SC-Distance (PF, MX), pp. 52–55.
ICPR-v2-2002-GargPH #network: Bayesian Networks as Ensemble of Classifiers (AG, VP, TSH), pp. 779–784.
ICPR-v2-2002-GiacintoR #detection #multi #network: Intrusion Detection in Computer Networks by Multiple Classifier Systems (GG, FR), pp. 390–393.
ICPR-v2-2002-GuillametSV #image #matrix: Analyzing Non-Negative Matrix Factorization for Image Classification (DG, BS, JV), pp. 116–119.
ICPR-v2-2002-GuptaDD #automation #fault #feature model: Beam Search for Feature Selection in Automatic SVM Defect Classification (PG, DSD, DD), pp. 212–215.
ICPR-v2-2002-GuunterB #recognition: A New Combination Scheme for HMM-Based Classififiers and its Application to Handwriting Recognition (SG, HB), pp. 332–337.
ICPR-v2-2002-Han #using: A Supervised Classification Scheme Using Positive Boolean Function (CCH), pp. 100–103.
ICPR-v2-2002-HuangT #fault #pattern matching #pattern recognition #recognition: An RBF-Based Pattern Recognition Method by Competitively Reducing Classification-Oriented Error (YSH, YHT), pp. 180–183.
ICPR-v2-2002-HungYL #image #using: Use of Characteristic Views in Image Classification (CCH, SY, CML), pp. 949–952.
ICPR-v2-2002-JainM #kernel: Hierarchical Kernel Fitting for Fingerprint Classification and Alignment (AKJ, SM), pp. 469–473.
ICPR-v2-2002-KimPJKB #using: Pattern Classification Using Support Vector Machine Ensemble (HCK, SP, HMJ, DK, SYB), pp. 160–163.
ICPR-v2-2002-LoogG #segmentation: Supervised Segmentation by Iterated Contextual Pixel Classification (ML, BvG), pp. 925–928.
ICPR-v2-2002-MesserCK #automation: Automatic Sports Classification (KM, WJC, JK), pp. 1005–1008.
ICPR-v2-2002-MurpheyL #feature model #multi #network: Feature Extraction for a Multiple Pattern Classification Neural Network System (YLM, YL), pp. 220–223.
ICPR-v2-2002-Paletta #detection #using: Detection of Traffic Signs Using Posterior Classifier Combination (LP), pp. 705–708.
ICPR-v2-2002-PernerPM: Texture Classification Based on the Boolean Model and its Application to Hep-2 Cells (PP, HP, BM), pp. 406–409.
ICPR-v2-2002-RasheedS: Movie Genre Classification By Exploiting Audio-Visual Features Of Previews (ZR, MS), pp. 1086–1089.
ICPR-v2-2002-RidderPD #complexity #fault: The Economics of Classification: Error vs. Complexity (DdR, EP, RPWD), pp. 244–247.
ICPR-v2-2002-RoliFV #analysis #trade-off: Analysis of Error-Reject Trade-off in Linearly Combined Classifiers (FR, GF, GV), pp. 120–125.
ICPR-v2-2002-RonnebergerBS #3d #invariant #recognition #set #using: General-Purpose Object Recognition in 3D Volume Data Sets Using Gray-Scale Invariants --- Classification of Airborne Pollen-Grains Recorded with a Confocal Laser Scanning Microscope (OR, HB, ES), p. 290–?.
ICPR-v2-2002-RyazanovV #approach #automation #scalability: Discrete Approach for Automatic Knowledge Extraction from Precedent Large-Scale Data, and Classification (VVR, VAV), pp. 188–191.
ICPR-v2-2002-Schiele #how #question: How Many Classifiers Do I Need? (BS), pp. 176–179.
ICPR-v2-2002-SirlantzisFG #algorithm #multi: An Evolutionary Algorithm for Classifier and Combination Rule Selection in Multiple Classifier Systems (KS, MCF, RMG), pp. 771–774.
ICPR-v2-2002-StefanoCM #adaptation #multi: An Adaptive Weighted Majority Vote Rule for Combining Multiple Classifiers (CDS, ADC, AM), pp. 192–195.
ICPR-v2-2002-TassoneWV: Temporal PDMs for Gait Classification (ET, GAWW, SV), pp. 1065–1068.
ICPR-v2-2002-TaxD #multi #using: Using Two-Class Classifiers for Multiclass Classification (DMJT, RPWD), pp. 124–127.
ICPR-v2-2002-Vaswani #linear #matrix: A Linear Classifier for Gaussian Class Conditional Distributions with Unequal Covariance Matrices (NV), pp. 60–63.
ICPR-v2-2002-VeeramachaneniFLN #polynomial: Style-Conscious Quadratic Field Classifier (SV, HF, CLL, GN), pp. 72–75.
ICPR-v3-2002-BaesensECV #learning #markov #monte carlo #network #using: Learning Bayesian Network Classifiers for Credit Scoring Using Markov Chain Monte Carlo Search (BB, MEP, RC, JV), pp. 49–52.
ICPR-v3-2002-BurschkaH: Scene Classification from Dense Disparity Maps in Indoor Environments (DB, GDH), pp. 708–712.
ICPR-v3-2002-GorgevikC #recognition: Combining SVM Classifiers for Handwritten Digit Recognition (DG, DC), pp. 102–105.
ICPR-v3-2002-HoqueFG #learning #performance: The Effect of the Inhibition-Compensation Learning Scheme on n-tuple Based Classifier Performance (SH, MCF, RMG), pp. 452–455.
ICPR-v3-2002-KuritaTI #image #network: A Neural Network Classifier for Occluded Images (TK, TT, YI), pp. 45–48.
ICPR-v3-2002-Kwon #clustering #using: Hangul Tree Classifier for Type Clustering Using Horizontal and Vertical Strokes (YBK), pp. 228–231.
ICPR-v3-2002-LefevreMV #process #segmentation: A Two Level Classifier Process for Audio Segmentation (SL, BM, NV), pp. 891–894.
ICPR-v3-2002-LiangDMG #logic: Page Classification through Logical Labelling (JL, DSD, MYM, JKG), pp. 477–480.
ICPR-v3-2002-PengHD #adaptation #kernel #metric #nearest neighbour: Adaptive Kernel Metric Nearest Neighbor Classification (JP, DRH, HKD), pp. 33–36.
ICPR-v3-2002-QiP: Context-Sensitive Bayesian Classifiers and Application to Mouse Pressure Pattern Classification (Y(Q, RWP), pp. 448–451.
ICPR-v3-2002-RivlinRGBL #realtime: A Real-Time System for Classification of Moving Objects (ER, MR, RG, UB, SL), pp. 688–691.
ICPR-v3-2002-RodriguezSAP #incremental: An Incremental and Hierarchical K-NN Classifier for Handwritten Characters (CR, FBS, ISA, AP), pp. 98–101.
ICPR-v3-2002-SahbiB #detection: Coarse-to-Fine Support Vector Classifiers for Face Detection (HS, NB), pp. 359–362.
ICPR-v3-2002-SiggelkowB #image #retrieval: Improvement of Histogram-Based Image Retrieval and Classification (SS, HB), pp. 367–370.
ICPR-v3-2002-SilvestreL #bound #optimisation: Optimization of Neural Classifiers Based on Bayesian Decision Boundaries and Idle Neurons Pruning (MRS, LLL), pp. 387–390.
ICPR-v3-2002-WangBR #recognition #word: Combining HMM-Based Two-Pass Classifiers for Off-Line Word Recognition (WW, AB, GR), pp. 151–154.
ICPR-v3-2002-WangCZ #automation #documentation #image: Hierarchical Content Classification and Script Determination for Automatic Document Image Processing (QW, ZC, RZ), pp. 77–80.
ICPR-v3-2002-WangPH #documentation: A Method for Document Zone Content Classification (YW, ITP, RMH), p. 196–?.
ICPR-v3-2002-XueG #performance #predict #word: Performance Prediction for Handwritten Word Recognizers and Its Application to Classifier Combination (HX, VG), pp. 241–244.
ICPR-v3-2002-Yang: Extended Isomap for Classification (MHY), pp. 615–618.
ICPR-v4-2002-BarataP02a #clustering #modelling #set #using: Improving Classification Rates by Modelling the Clusters of Trainings Sets in Features Space Using Mathematical Morphology Operators (TB, PP), pp. 90–93.
ICPR-v4-2002-CaputoN #kernel: To Each According to its Need: Kernel Class Specific Classifiers (BC, HN), pp. 94–97.
ICPR-v4-2002-HoogsCK #3d #metaprogramming #using: Classification of 3D Macro Texture Using Perceptual Observables (AH, RC, RK), pp. 113–117.
ICPR-v4-2002-LiuSF #learning #polynomial: Learning Quadratic Discriminant Function for Handwritten Character Classification (CLL, HS, HF), pp. 44–47.
ICPR-v4-2002-MathisB #approach #using: Classification Using a Hierarchical Bayesian Approach (CM, TMB), p. 103–?.
ICPR-v4-2002-MottlKK #identification #kernel: Support Object Classifiers with Rigid and Elastic Kernel Functions for Face Identification (VM, AK, JK), pp. 205–208.
ICPR-v4-2002-PerisM #distance #edit distance #performance: Fast Cyclic Edit Distance Computation with Weighted Edit Costs in Classification (GP, AM), pp. 184–187.
ICPR-v4-2002-Sarkar #algorithm: An Iterative Algorithm for Optimal Style Conscious Field Classification (PS), p. 243–?.
ICPR-v4-2002-SerranoSL #approach #performance: A Computationally Efficient Approach to Indoor/Outdoor Scene Classification (NS, AES, JL), p. 146–?.
ICPR-v4-2002-TothCA #fault: A Two-Stage-Classifier for Defect Classification in Optical Media Inspection (DT, AC, TA), pp. 373–376.
KDD-2002-Aggarwal #effectiveness #on the #string: On effective classification of strings with wavelets (CCA), pp. 163–172.
KDD-2002-DhillonMK #clustering #word: Enhanced word clustering for hierarchical text classification (ISD, SM, RK), pp. 191–200.
KDD-2002-FragoudisML: Integrating feature and instance selection for text classification (DF, DM, SL), pp. 501–506.
KDD-2002-KolczSK #performance #random: Efficient handling of high-dimensional feature spaces by randomized classifier ensembles (AK, XS, JKK), pp. 307–313.
KDD-2002-KruengkraiJ #algorithm #learning #parallel: A parallel learning algorithm for text classification (CK, CJ), pp. 201–206.
KDD-2002-LiB #algorithm: Instability of decision tree classification algorithms (RHL, GGB), pp. 570–575.
KDD-2002-LiTS #robust #set: Construct robust rule sets for classification (JL, RWT, HS), pp. 564–569.
KDD-2002-LiuL #adaptation #documentation #incremental #mining: Incremental context mining for adaptive document classification (RLL, YLL), pp. 599–604.
KDD-2002-Olecka #performance: Evaluating classifiers’ performance in a constrained environment (AO), pp. 605–612.
KDD-2002-RaskuttiFK #clustering #using: Combining clustering and co-training to enhance text classification using unlabelled data (BR, HLF, AK), pp. 620–625.
KDD-2002-UgurelKG #automation #source code #what: What’s the code?: automatic classification of source code archives (SU, RK, CLG), pp. 639–644.
KDD-2002-VlachosDGKK #reduction #visualisation: Non-linear dimensionality reduction techniques for classification and visualization (MV, CD, DG, GK, NK), pp. 645–651.
KDD-2002-WuFS #approach #data mining #mining #named: B-EM: a classifier incorporating bootstrap with EM approach for data mining (XW, JF, KRS), pp. 670–675.
KDD-2002-YuHC #learning #named #using #web: PEBL: positive example based learning for Web page classification using SVM (HY, JH, KCCC), pp. 239–248.
KDD-2002-ZadroznyE #multi #probability: Transforming classifier scores into accurate multiclass probability estimates (BZ, CE), pp. 694–699.
SEKE-2002-Morasca #using: A proposal for using continuous attributes in classification trees (SM), pp. 417–424.
SEKE-2002-NakkrasaeS #approach #component #formal method #specification: A formal approach for specification and classification of software components (SN, PS), pp. 773–780.
SIGIR-2002-BennettDH #modelling #probability #reliability #using: Probabilistic combination of text classifiers using reliability indicators: models and results (PNB, STD, EH), pp. 207–214.
SIGIR-2002-Boyapati #using: Improving hierarchical text classification using unlabeled data (VB), pp. 363–364.
SIGIR-2002-ChaiCN #online: Bayesian online classifiers for text classification and filtering (KMAC, HLC, HTN), pp. 97–104.
SIGIR-2002-HardySSTZW #concept #summary: Cross-document summarization by concept classification (HH, NS, TS, TL, XZ, GBW), pp. 121–128.
SIGIR-2002-KimRL #estimation #multi #naive bayes #parametricity: A new method of parameter estimation for multinomial naive bayes text classifiers (SBK, HCR, HSL), pp. 391–392.
SIGIR-2002-KouG #algorithm: Study of category score algorithms for k-NN classifier (HK, GG), pp. 393–394.
SIGIR-2002-LeeM: Text genre classification with genre-revealing and subject-revealing features (YBL, SHM), pp. 145–150.
SIGIR-2002-SlonimFT #documentation #using: Unsupervised document classification using sequential information maximization (NS, NF, NT), pp. 129–136.
SIGIR-2002-Wolin #automation: Automatic classification in product catalogs (BW), pp. 351–352.
PLDI-2002-BurtscherDH #predict: Static Load Classification for Improving the Value Predictability of Data-Cache Misses (MB, AD, MH), pp. 222–233.
SAC-2002-CrescenziMM #web: Wrapping-oriented classification of web pages (VC, GM, PM), pp. 1108–1112.
SAC-2002-DingDP #data type #using: Decision tree classification of spatial data streams using Peano Count Trees (QD, QD, WP), pp. 413–417.
SAC-2002-NevesBR #game studies #learning: Learning the risk board game with classifier systems (AN, OB, ACR), pp. 585–589.
ECDL-2001-FuhrHMMS #evaluation #library: Digital Libraries: A Generic Classification and Evaluation Scheme (NF, PH, MM, AM, IS), pp. 187–199.
ECDL-2001-MatthesNS #named: C-Merge: A Tool for Policy-Based Merging of Resource Classifications (FM, CN, US), pp. 352–365.
ECDL-2001-SemeraroFFE #documentation #modelling: Document Classification and Interpretation through the Inference of Logic-Based Models (GS, SF, NF, FE), pp. 59–70.
ICDAR-2001-AkselaLOK #adaptation: Rejection Methods for an Adaptive Committee Classifier (MA, JL, EO, JK), pp. 982–986.
ICDAR-2001-BagdanovW #documentation #fine-grained #first-order #graph #random #using: Fine-Grained Document Genre Classification Using First Order Random Graphs (ADB, MW), pp. 79–85.
ICDAR-2001-BarakatB #geometry: Training with Positive and Negative Data Samples: Effects on a Classifier for Hand-Drawn Geometric Shapes (HB, DB), pp. 1017–1021.
ICDAR-2001-CesariniLMS #documentation #encoding: Encoding of Modified X-Y Trees for Document Classification (FC, ML, SM, GS), pp. 1131–1136.
ICDAR-2001-ChaS #algorithm #analysis: Apriori Algorithm for Sub-category Classification Analysis of Handwriting (SHC, SNS), pp. 1022–1025.
ICDAR-2001-DaWM #analysis #fuzzy: Character Preclassification Based on Fuzzy Typographical Analysis (LD, PW, BM), pp. 74–78.
ICDAR-2001-DiligentiGMS #documentation #html #modelling: Classification of HTML Documents by Hidden Tree-Markov Models (MD, MG, MM, FS), pp. 849–853.
ICDAR-2001-HoN #constraints: Exploration of Contextual Constraints for Character Pre-Classification (TKH, GN), pp. 450–454.
ICDAR-2001-HoqueF #learning: An Improved Learning Scheme for the Moving Window Classifier (SH, MCF), pp. 607–611.
ICDAR-2001-KangL #multi: Experimental Results on the Construction of Multiple Classifiers Recognizing Handwritten Numerals (HJK, SWL), pp. 1026–1030.
ICDAR-2001-NatteeN #comprehension #documentation #geometry #machine learning #online #using: Geometric Method for Document Understanding and Classification Using On-line Machine Learning (CN, MN), pp. 602–606.
ICDAR-2001-Ratzlaff #online #recognition: A Scanning n-tuple Classifier for Online Recognition of Handwritten Digits (EHR), pp. 18–22.
ICDAR-2001-SerraduraSV #markov #modelling #using #web: Web Sites Thematic Classification Using Hidden Markov Models (LS, MS, NV), pp. 1094–1099.
ICDAR-2001-SirlantzisF #configuration management #multi #novel #recognition #self: Investigation of a Novel Self-configurable Multiple Classifier System for Character Recognition (KS, MCF), pp. 1002–1006.
ICDAR-2001-TeredesaiG #approach #optimisation: Active Digit Classifiers: A Separability Optimization Approach to Emulate Cognition (AT, VG), pp. 401–405.
ICDAR-2001-WangHP01a #evaluation #performance: Zone Content Classification and its Performance Evaluation (YW, RMH, ITP), pp. 540–544.
ICDAR-2001-WengH #image #incremental #online: Incremental Hierarchical Discriminant Regression for Online Image Classification (JW, WSH), pp. 476–480.
ICDAR-2001-YeCS #reduction #using: Reduction of the Classification Cost Using Hierarchical Classifiers based on the k-NN Rule (XY, MC, CYS), pp. 716–720.
JCDL-2001-LiuW #automation #feature model: Feature selection for automatic classification of musical instrument sounds (ML, CW), pp. 247–248.
JCDL-2001-PanFV #mining #named #video: VideoGraph: a new tool for video mining and classification (JYP, CF), pp. 116–117.
ICSM-2001-BassinS #fault #legacy #maintenance #orthogonal #outsourcing: Managing the Maintenance of Ported, Outsourced, and Legacy Software via Orthogonal Defect Classification (KB, PS), p. 726–?.
ICEIS-v1-2001-RobardetV #case study: A Preliminary Study of a New Classification to Build Homogeneous Patient’s Groups in Home-Based Care (CR, CV), pp. 397–403.
CIKM-2001-Al-KofahiTVTJ #categorisation #multi: Combining Multiple Classifiers for Text Categorization (KAK, AT, AV, TT, PJ), pp. 97–104.
CIKM-2001-GohCC #image: SVM Binary Classifier Ensembles for Image Classification (KG, EYC, KTC), pp. 395–402.
CIKM-2001-NottelmannF #datalog #learning #probability: Learning Probabilistic Datalog Rules for Information Classification and Transformation (HN, NF), pp. 387–394.
CIKM-2001-SattlerD #database #sql: SQL Database Primitives for Decision Tree Classifiers (KUS, OD), pp. 379–386.
CIKM-2001-ToutanovaCPH #set: Text Classification in a Hierarchical Mixture Model for Small Training Sets (KT, FC, KP, TH), pp. 105–112.
CIKM-2001-ZelikovitzH #using: Using LSI for Text Classification in the Presence of Background Text (SZ, HH), pp. 113–118.
ICML-2001-DobraG #bias: Bias Correction in Classification Tree Construction (AD, JG), pp. 90–97.
ICML-2001-DomeniconiG #approach #approximate #dataset #multi #nearest neighbour #performance #query #scalability: An Efficient Approach for Approximating Multi-dimensional Range Queries and Nearest Neighbor Classification in Large Datasets (CD, DG), pp. 98–105.
ICML-2001-GartnerF #named: WBCsvm: Weighted Bayesian Classification based on Support Vector Machines (TG, PAF), pp. 154–161.
ICML-2001-LangfordSM #bound #predict: An Improved Predictive Accuracy Bound for Averaging Classifiers (JL, MWS, NM), pp. 290–297.
ICML-2001-LatinneSD #multi #problem: Adjusting the Outputs of a Classifier to New a Priori Probabilities May Significantly Improve Classification Accuracy: Evidence from a multi-class problem in remote sensing (PL, MS, CD), pp. 298–305.
ICML-2001-NgJ #convergence #feature model: Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection (AYN, MIJ), pp. 377–384.
ICML-2001-RozsypalK #algorithm #nearest neighbour #search-based #using: Using the Genetic Algorithm to Reduce the Size of a Nearest-Neighbor Classifier and to Select Relevant Attributes (AR, MK), pp. 449–456.
ICML-2001-SebbanNL: Boosting Neighborhood-Based Classifiers (MS, RN, SL), pp. 505–512.
ICML-2001-ShakhnarovichEB #evaluation #statistics: Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation (GS, REY, YB), pp. 521–528.
ICML-2001-ZadroznyE #naive bayes #probability: Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers (BZ, CE), pp. 609–616.
KDD-2001-BujaL #data mining #mining: Data mining criteria for tree-based regression and classification (AB, YSL), pp. 27–36.
KDD-2001-CarageaCH #using: Gaining insights into support vector machine pattern classifiers using projection-based tour methods (DC, DC, VH), pp. 251–256.
KDD-2001-FungM: Proximal support vector machine classifiers (GF, OLM), pp. 77–86.
KDD-2001-IndurkhyaW #problem #rule-based: Solving regression problems with rule-based ensemble classifiers (NI, SMW), pp. 287–292.
KDD-2001-MoodySV #automation: Data filtering for automatic classification of rocks from reflectance spectra (JM, RBdAeS, JV), pp. 347–352.
KDD-2001-StreetK #algorithm #scalability #streaming: A streaming ensemble algorithm (SEA) for large-scale classification (WNS, YK), pp. 377–382.
MLDM-2001-Krzyzak #learning #network #using: Nonlinear Function Learning and Classification Using Optimal Radial Basis Function Networks (AK), pp. 217–225.
MLDM-2001-MottlDSKM #pattern matching #pattern recognition #recognition: Featureless Pattern Recognition in an Imaginary Hilbert Space and Its Application to Protein Fold Classification (VM, SD, OS, CAK, IBM), pp. 322–336.
MLDM-2001-Perner #question #reasoning: Are Case-Based Reasoning and Dissimilarity-Based Classification Two Sides of the Same Coin? (PP), pp. 35–51.
MLDM-2001-PhamWS #detection #network: Face Detection by Aggregated Bayesian Network Classifiers (TVP, MW, AWMS), pp. 249–262.
SEKE-2001-MorenoS #detection #requirements: A Method for Detection, Classification and Resolution of Discrepancies in Viewpoint-based Requirements Engineering (AMM, AS), pp. 110–119.
SIGIR-2001-ArampatzisH #adaptation #optimisation: The Score-Distributional Threshold Optimization for Adaptive Binary Classification Tasks (AA, AvH), pp. 285–293.
SIGIR-2001-DrewL #using: Construction of a Hierarchical Classifier Schema Using a Combination of Text-Based and Image-Based Approaches (MSD, CL), pp. 438–439.
SIGIR-2001-Joachims #learning #statistics: A Statistical Learning Model of Text Classification for Support Vector Machines (TJ), pp. 128–136.
SIGIR-2001-OakesGF #documentation: A Method Based on the Chi-Square Test for Document Classification (MPO, RJG, HF), pp. 440–441.
SIGIR-2001-StokesC #detection #documentation #semantics: Combining Semantic and Syntactic Document Classifiers to Improve First Story Detection (NS, JC), pp. 424–425.
ECOOP-2001-DrossopoulouDDG: Fickle : Dynamic Object Re-classification (SD, FD, MDC, PG), pp. 130–149.
DATE-2001-OlbrichRB #algorithm #analysis: An improved hierarchical classification algorithm for structural analysis of integrated circuits (MO, AR, EB), p. 807.
CBSE-2000-ThomasonBL #architecture #component: CLARiFi An Architecture for Component Classification and Brokerage (ST, PB, SL), p. 17.
ECDL-2000-Pasquier #automation #database #functional #library #order #topic: Functional and Intentional Limitations of Interactivity on Content Indexing Topics: Possible Uses of Automatic Classification and Contents Extraction Systems, in Order to Create Digital Libraries Databases (FP), pp. 219–228.
VLDB-2000-LuL #scalability: Decision Tables: Scalable Classification Exploring RDBMS Capabilities (HL, HL), pp. 373–384.
IWPC-2000-GirardW #approach #data type #detection: Evaluating the Accessor Classification Approach to Detect Abstract Data Types (JFG, MW), pp. 87–95.
ICEIS-2000-Sato-Ilic #fuzzy #relational: Classification Based on Relational Fuzzy C-Means for 3-Way Data (MSI), pp. 217–221.
CIKM-2000-MeretakisFLL #scalability: Scalable association-based text classification (DM, DF, HL, SL), pp. 5–11.
ICML-2000-AllweinSS #approach #multi: Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers (ELA, RES, YS), pp. 9–16.
ICML-2000-BennettB #geometry: Duality and Geometry in SVM Classifiers (KPB, EJB), pp. 57–64.
ICML-2000-BowersGL: Classification of Individuals with Complex Structure (AFB, CGGC, JWL), pp. 81–88.
ICML-2000-BrutlagM #challenge #email: Challenges of the Email Domain for Text Classification (JDB, CM), pp. 103–110.
ICML-2000-CampbellCS #learning #query #scalability: Query Learning with Large Margin Classifiers (CC, NC, AJS), pp. 111–118.
ICML-2000-Domingos #problem: Bayesian Averaging of Classifiers and the Overfitting Problem (PMD), pp. 223–230.
ICML-2000-Ghani #using: Using Error-Correcting Codes for Text Classification (RG), pp. 303–310.
ICML-2000-HsuHW #naive bayes #why: Why Discretization Works for Naive Bayesian Classifiers (CNH, HJH, TTW), pp. 399–406.
ICML-2000-JuKS #gesture: State-based Classification of Finger Gestures from Electromyographic Signals (PJ, LPK, YS), pp. 439–446.
ICML-2000-KaynakA #multi: MultiStage Cascading of Multiple Classifiers: One Man’s Noise is Another Man’s Data (CK, EA), pp. 455–462.
ICML-2000-KubatC #nearest neighbour #subclass: Voting Nearest-Neighbor Subclassifiers (MK, MCJ), pp. 503–510.
ICML-2000-MargineantuD #evaluation: Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers (DDM, TGD), pp. 583–590.
ICML-2000-MullinS #nearest neighbour: Complete Cross-Validation for Nearest Neighbor Classifiers (MDM, RS), pp. 639–646.
ICML-2000-TongK #learning: Support Vector Machine Active Learning with Application sto Text Classification (ST, DK), pp. 999–1006.
ICML-2000-VilaltaO #bias #distance #evaluation #metric #quantifier: A Quantification of Distance Bias Between Evaluation Metrics In Classification (RV, DO), pp. 1087–1094.
ICML-2000-WesterdijkW #modelling #multi #using: Classification with Multiple Latent Variable Models using Maximum Entropy Discrimination (MW, WW), pp. 1143–1150.
ICML-2000-WilliamsS #kernel: The Effect of the Input Density Distribution on Kernel-based Classifiers (CKIW, MWS), pp. 1159–1166.
ICML-2000-ZelikovitzH #problem #using: Improving Short-Text Classification using Unlabeled Data for Classification Problems (SZ, HH), pp. 1191–1198.
ICPR-v1-2000-ClavierTLDL #sorting: Classifiers Combination for Forms Sorting (EC, ÉT, ML, SD, JL), pp. 1932–1935.
ICPR-v1-2000-GongL #segmentation #video: Video Shot Segmentation and Classification (YG, XL), pp. 1860–1863.
ICPR-v1-2000-HeidemannLR #network #visual notation: A System for Various Visual Classification Tasks Based on Neural Networks (GH, DL, HJR), pp. 1009–1012.
ICPR-v1-2000-PaquisLK #using: Road Surface Classification by Thresholding Using Morphological Pyramid (SP, VL, HK), pp. 1334–1337.
ICPR-v1-2000-PrabhakarJWPB #verification: Minutia Verification and Classification for Fingerprint Matching (SP, AKJ, JW, SP, RMB), pp. 1025–1029.
ICPR-v1-2000-SinghMH #image #segmentation: FLIR Image Segmentation and Natural Object Classification (SS, MM, JFH), pp. 1681–1684.
ICPR-v1-2000-YangM #gender #visual notation: Support Vector Machines for Visual Gender Classification (MHY, BM), pp. 5115–5118.
ICPR-v2-2000-Abe #fuzzy: Generalization Improvement of a Fuzzy Classifier with Pyramidal Membership Functions (SA), pp. 2211–2214.
ICPR-v2-2000-AlexandreCK #independence #using: Combining Independent and Unbiased Classifiers Using Weighted Average (LAA, ACC, MSK), pp. 2495–2498.
ICPR-v2-2000-BaggenstossN #probability #using: A Theoretically Optimal Probabilistic Classifier Using Class-Specific Features (PMB, HN), pp. 2763–2768.
ICPR-v2-2000-BeiraghiAAS #fault #fuzzy #recognition: Application of Fuzzy Integrals in Fusion of Classifiers for Low Error Rate Handwritten Numerals Recognition (SB, MA, MASA, MS), pp. 2487–2490.
ICPR-v2-2000-ChazalR #comparison #using: A Comparison of the Use of Different Wavelet Coefficients for the Classification of the Electrocardiogram (PdC, RBR), pp. 2255–2258.
ICPR-v2-2000-ChoKBBY #image: Core-Based Fingerprint Image Classification (BHC, JSK, JHB, IGB, KYY), pp. 2859–2862.
ICPR-v2-2000-ChouS #algorithm #learning #multi: A Hierarchical Multiple Classifier Learning Algorithm (YYC, LGS), pp. 2152–2155.
ICPR-v2-2000-Duin: Classifiers in Almost Empty Spaces (RPWD), pp. 2001–2007.
ICPR-v2-2000-GaoD #algorithm #feature model #on the: On Improvement of Feature Extraction Algorithms for Discriminative Pattern Classification (JG, XD), pp. 2101–2104.
ICPR-v2-2000-GiacintoR #framework: A Theoretical Framework for Dynamic Classifier Selection (GG, FR), pp. 2008–2011.
ICPR-v2-2000-GiacintoRF #clustering #design #effectiveness #multi: Design of Effective Multiple Classifier Systems by Clustering of Classifiers (GG, FR, GF), pp. 2160–2163.
ICPR-v2-2000-GoodeG #parametricity: Semi-Parametric Signal Classification (AJG, RHG), pp. 2622–2625.
ICPR-v2-2000-HamadaSHT #automation #image: Automated Construction of Image Processing Procedure Based on Misclassification Condition (TH, AS, JiH, JiT), pp. 2430–2433.
ICPR-v2-2000-HoB #complexity #problem: Measuring the Complexity of Classification Problems (TKH, MB), pp. 2043–2047.
ICPR-v2-2000-HuangCSG #nearest neighbour #prototype: Constructing Optimized Prototypes for Nearest Neighbor Classifiers (YSH, CCC, JWS, WELG), pp. 2017–2020.
ICPR-v2-2000-JuanV #edit distance #normalisation #on the #performance #string #using: On the Use of Normalized Edit Distances and an Efficient k-NN Search Technique (k-AESA) for Fast and Accurate String Classification (AJ, EV), pp. 2676–2679.
ICPR-v2-2000-Kangas #comparison #nearest neighbour #prototype #representation: Comparison between Two Prototype Representation Schemes for a Nearest Neighbor Classifier (JK), pp. 2773–2776.
ICPR-v2-2000-KangL #multi: An Information-Theoretic Strategy for Constructing Multiple Classifier Systems (HJK, SWL), pp. 2483–2486.
ICPR-v2-2000-KeglKN #complexity #learning #network: Radial Basis Function Networks and Complexity Regularization in Function Learning and Classification (BK, AK, HN), pp. 2081–2086.
ICPR-v2-2000-KimKNS #recognition #word: A Methodology of Combining HMM and MLP Classifiers for Cursive Word Recognition (JHK, KKK, CPN, CYS), pp. 2319–2322.
ICPR-v2-2000-KudoIS: A Histogram-Based Classifier on Overlapped Bins (MK, HI, MS), pp. 2029–2033.
ICPR-v2-2000-KunchevaWSD #independence #question: Is Independence Good For Combining Classifiers? (LIK, CJW, CAS, RPWD), pp. 2168–2171.
ICPR-v2-2000-MalekTA #fault: Effect of the Feature Vector Size on the Generalization Error: The Case of MLPNN and RBFNN Classifiers (JEM, RT, AMA), pp. 2630–2633.
ICPR-v2-2000-Martinez-HinarejosJC #string #using: Use of Median String for Classification (CDMH, AJ, FC), pp. 2903–2906.
ICPR-v2-2000-MascarillaF: Another Look at Combining Rejection-Based Pattern Classifiers (LM, CF), pp. 2156–2159.
ICPR-v2-2000-MatsakisW: Orbit and Sinus Classification Based on Force Histogram Computation (PM, LW), pp. 2451–2454.
ICPR-v2-2000-MetzlerAPL #image #matrix #multi: Texture Classification of Graylevel Images by Multiscale Cross-Cooccurrence Matrices (VM, TA, CP, TML), pp. 2549–2552.
ICPR-v2-2000-MitaniH #design #nearest neighbour #using: Classifier Design Based on the Use of Nearest Neighbor Samples (YM, YH), pp. 2769–2772.
ICPR-v2-2000-MiyamotoHM #design #polynomial #using: Use of Bootstrap Samples in Quadratic Classifier Design (TM, YH, YM), pp. 2789–2792.
ICPR-v2-2000-MollinedaFV #clustering #prototype: A Cluster-Based Merging Strategy for Nearest Prototype Classifiers (RAM, FJF, EV), pp. 2755–2758.
ICPR-v2-2000-MutoNH #evaluation: Evaluation of a Modified Parzen Classifier in High Dimensional Spaces (YM, HN, YH), pp. 2067–2070.
ICPR-v2-2000-NgB #segmentation #using: Supervised Texture Segmentation using DWT and a Modified K-NN Classifier (BWN, AB), pp. 2545–2548.
ICPR-v2-2000-PekalskaD #pattern matching #pattern recognition #recognition: Classifiers for Dissimilarity-Based Pattern Recognition (EP, RPWD), pp. 2012–2016.
ICPR-v2-2000-PerantonisPV #analysis #component #paradigm #using: Supervised Principal Component Analysis Using a Smooth Classifier Paradigm (SJP, SP, VV), pp. 2109–2112.
ICPR-v2-2000-Raudys #adaptation: Prior Weights in Adaptive Pattern Classification (SR), pp. 6010–6013.
ICPR-v2-2000-RibaCVJ #invariant: Methods for Invariant Signature Classification (JRR, AC, SV, IJ), pp. 2953–2956.
ICPR-v2-2000-SarkarN: Classification of Style-Constrained Pattern-Fields (PS, GN), pp. 2855–2858.
ICPR-v2-2000-Sato #fault #learning: A Learning Method for Definite Canonicalization Based on Minimum Classification Error (AS), pp. 2199–2202.
ICPR-v2-2000-Singh #locality: EEG Data Classification with Localized Structural Information (SS), pp. 2271–2274.
ICPR-v2-2000-Tambouratzis: Improving the Classification Accuracy of the Scanning n-tuple Method (GT), pp. 6046–6049.
ICPR-v2-2000-TangXM00a: Two-Step Classification Based on Scale Space (MT, JX, SM), pp. 2899–2902.
ICPR-v2-2000-VailayaJ: Reject Option for VQ-Based Bayesian Classification (AV, AKJ), pp. 2048–2051.
ICPR-v2-2000-VuoriLOK #adaptation #online #prototype: Controlling On-Line Adaptation of a Prototype-Based Classifier for Handwritten Characters (VV, JL, EO, JK), pp. 2331–2334.
ICPR-v2-2000-WohlerKA #image #recognition #sequence: Pedestrian Recognition by Classification of Image Sequences — Global Approaches vs. Local Spatio-Temporal Processing (CW, UK, JKA), pp. 2540–2544.
ICPR-v2-2000-WuZZ #network #recognition: A Neural Network Based Classifier for Handwritten Chinese Character Recognition (MW, BZ, LZ), pp. 2561–2564.
ICPR-v2-2000-XiaoWD #adaptation #recognition: Adaptive Combination of Classifiers and its Application to Handwritten Chinese Character Recognition (BX, CHW, RD), pp. 2327–2330.
ICPR-v2-2000-YuJB #recognition #visual notation: Combining Acoustic and Visual Classifiers for the Recognition of Spoken Sentences (KY, XJ, HB), pp. 2491–2494.
ICPR-v2-2000-ZhangDL #design #feature model #multi #recognition: Multi-Scale Feature Extraction and Nested-Subset Classifier Design for High Accuracy Handwritten Character Recognition (JZ, XD, CL), pp. 2581–2584.
ICPR-v3-2000-ChantlerM #invariant #on the #using: On the Use of Gradient Space Eigenvalues for Rotation Invariant Texture Classification (MJC, GM), pp. 3943–3946.
ICPR-v3-2000-ChetverikovF #invariant: Affine-Invariant Texture Classification (DC, ZF), pp. 3901–3904.
ICPR-v3-2000-GaoQL #fuzzy: Fuzzy Classification of Generic Edge Features (QG, DQ, SL), pp. 3672–3675.
ICPR-v3-2000-HuangCH #adaptation: An Adaptive Model for Texture Classification (YH, KLC, ZH), pp. 3905–3908.
ICPR-v3-2000-HufnaglU #fault #performance: Resolving a Defect in Quadrant-Based Classification for Fast Block-Matching (CH, AU), pp. 3203–3206.
ICPR-v3-2000-Kiema #automation #data fusion #using: Wavelet Compression and Data Fusion: An Investigation into the Automatic Classification of Urban Environments using Color Photography and Laser Scanning Data (JBKK), pp. 3089–3093.
ICPR-v3-2000-MaenpaaOPM #robust #set: Robust Texture Classification by Subsets of Local Binary Patterns (TM, TO, MP, MS), pp. 3947–3950.
ICPR-v3-2000-MaenpaaPO #multi: Texture Classification by Multi-Predicate Local Binary Pattern Operators (TM, MP, TO), pp. 3951–3954.
ICPR-v3-2000-MostafaPF: A Two-Step Fuzzy-Bayesian Classification for High Dimensional Data (MGHM, TCP, AAF), pp. 3421–3424.
ICPR-v3-2000-Ney #modelling #probability #recognition #speech: Stochastic Modeling: From Pattern Classification to Speech Recognition and Translation (HN), pp. 3025–3032.
ICPR-v3-2000-NgR #gesture #recognition: Gesture Recognition via Pose Classification (CWN, SR), pp. 3703–3708.
ICPR-v3-2000-SebeL00a: Wavelet Based Texture Classification (NS, MSL), pp. 3959–3962.
ICPR-v3-2000-VandenbrouckeMP #image #segmentation: Color Image Segmentation by Supervised Pixel Classification in a Color Texture Feature Space: Application to Soccer Image Segmentation (NV, LM, JGP), pp. 3625–3628.
ICPR-v3-2000-VertanB #normalisation #representation: Color Texture Classification by Normalized Color Space Representation (CV, NB), pp. 3584–3587.
ICPR-v3-2000-VriesV #3d #adaptation #detection #estimation #image: Scale-Adaptive Landmark Detection, Classification and Size Estimation in 3D Object-Background Images (RGdV, PWV), pp. 7026–7029.
ICPR-v4-2000-IwamotoTC #named #realtime: REFLICS: Real-Time Flow Imaging and Classification System (SI, MMT, DMCJ), pp. 4689–4692.
ICPR-v4-2000-KampelS: Color Classification of Archaeological Fragments (MK, RS), pp. 4771–4774.
ICPR-v4-2000-SanchezM #3d: Fusing 3D Information for Crop/Weeds Classification (AJS, JAM), pp. 4295–4298.
KDD-2000-AnkerstEK #effectiveness #towards: Towards an effective cooperation of the user and the computer for classification (MA, ME, HPK), pp. 179–188.
KDD-2000-FungM: Data selection for support vector machine classifiers (GF, OLM), pp. 64–70.
KDD-2000-InselbergA #visualisation: Classification and visualization for high-dimensional data (AI, TA), pp. 370–374.
KDD-2000-WangMSW #biology #case study #data mining #mining #network #sequence: Application of neural networks to biological data mining: a case study in protein sequence classification (JTLW, QM, DS, CHW), pp. 305–309.
KDD-2000-YiS #documentation: A classifier for semi-structured documents (JY, NS), pp. 340–344.
SIGIR-2000-DumaisC #web: Hierarchical classification of Web content (STD, HC), pp. 256–263.
SIGIR-2000-KimHZ #naive bayes: Text filtering by boosting naive bayes classifiers (YHK, SYH, BTZ), pp. 168–175.
SIGIR-2000-ManevitzY #documentation #network #using: Document classification on neural networks using only positive examples (LMM, MY), pp. 304–306.
SIGIR-2000-TakasuA #categorisation #comparison: Variance based classifier comparison in text categorization (AT, KA), pp. 316–317.
FSE-2000-NaumovichC: Classifying properties: an alternative to the safety-liveness classification (GN, LAC), pp. 159–168.
SAC-2000-ByunL #using: Form Classification Using DP Matching (YB, YL), pp. 1–4.
SAC-2000-KloseKST #fault #symmetry: Controlling Asymmetric Errors in Neuro-Fuzzy Classification (AK, RK, KS, UT), pp. 505–509.
HPCA-2000-HaungsSF #analysis #branch #metric: Branch Transition Rate: A New Metric for Improved Branch Classification Analysis (MH, PS, MKF), pp. 241–250.
STOC-2000-GuptaT #algorithm #approximate #constant #problem: A constant factor approximation algorithm for a class of classification problems (AG, ÉT), pp. 652–658.
ISSTA-2000-KolanoK #analysis #realtime: Classification schemes to aid in the analysis of real-time systems (PZK, RAK), pp. 86–95.
DL-1999-AbbadeniZW #image #retrieval #web: Image Classification and Retrieval on the World Wide Web (NA, DZ, SW), pp. 208–209.
DL-1999-ArdoK #automation: Creation and Automatic Classification of a Robot-Generated Subject Index (AA, TK), pp. 210–211.
DL-1999-Larkey: A Patent Search and Classification System (LSL), pp. 179–187.
DL-1999-Lim #image #keyword #visual notation: Learnable Visual Keywords for Image Classification (JHL), pp. 139–145.
ICDAR-1999-AtukoraleS: Combining Classifiers based on Confidence Values (ASA, PNS), pp. 37–40.
ICDAR-1999-ClavierCL #approach #image #sorting: Image Sorting — Image Classification: A Global Approach (EC, SC, JL), pp. 123–126.
ICDAR-1999-DehkordiSW #approach #component #word: A Principal Component Approach to Classification of Handwritten Words (MED, NS, RJW), pp. 781–784.
ICDAR-1999-Hobby #composition #geometry #layout: Page Decomposition and Signature Finding via Shape Classification and Geometric Layout (JDH), pp. 555–558.
ICDAR-1999-HuKW #comparison #documentation #image #layout: Document Image Layout Comparison and Classification (JH, RSK, GTW), pp. 285–288.
ICDAR-1999-JungSS #multi #using: Multifont Classification using Typographical Attributes (MCJ, YCS, SNS), pp. 353–356.
ICDAR-1999-KangL #fault: Combining Classifiers based on Minimization of a Bayes Error Rate (HJK, SWL), pp. 398–401.
ICDAR-1999-Kawatani #recognition #using: Handwritten Kanji Recognition using Combined Complementary Classifiers in a Cascade Arrangement (TK), pp. 503–506.
ICDAR-1999-LeeG #automation: Automatic Classification of Deformed Handwritten Numeral Characters (LLL, NRG), pp. 269–272.
ICDAR-1999-LiN #documentation #learning: A Document Classification and Extraction System with Learning Ability (XL, PAN), pp. 197–200.
ICDAR-1999-LiuN99a #algorithm #learning #nearest neighbour #prototype #recognition: Prototype Learning Algorithms for Nearest Neighbor Classifier with Application to Handwritten Character Recognition (CLL, MN), pp. 378–381.
ICDAR-1999-RibertLE #design #distributed #performance #recognition: Designing Efficient Distributed Neural Classifiers: Application to Handwritten Digit Recognition (AR, YL, AE), pp. 265–268.
ICDAR-1999-StockerRL #network #problem #self: Self-organized Classification Problem Solving with Yprel Neural Networks (ES, AR, YL), pp. 390–393.
ICDAR-1999-WuS #distance #multi #network #recognition #using: Unconstrained Handwritten Numeral Recognition using Hausdorff Distance and Multi-Layer Neural Network Classifier (XW, PS), pp. 249–252.
VLDB-1999-WangZL #proximity #using: Building Hierarchical Classifiers Using Class Proximity (KW, SZ, SCL), pp. 363–374.
ICSM-1999-MendoncaK #component #comprehension #distributed: Component Module Classification for Distributed Software Understanding (NCM, JK), p. 119–?.
HCI-CCAD-1999-NisslerMH #3d #design #how: How to get the right outfit for my agent? Classification — and design methodology for a virtual shopping assistant in a 3D world (JN, JM, AH), pp. 162–166.
HCI-EI-1999-HartsonAWR #framework #problem #usability: The User Action Framework: A Theory-Based Foundation for Inspection and Classification of Usability Problems (HRH, TSA, RCW, LvR), pp. 1058–1062.
HCI-EI-1999-KandaN #visual notation: Studies on Classification of Similar Trademarks Corresponding to Human Visual Cognitive Sense (TK, HN), pp. 501–505.
CAiSE-1999-BeckerM #framework #towards #workflow: Towards a Classification Framework for Application Granularity in Workflow Management Systems (JB, MzM), pp. 411–416.
CIKM-1999-DolinPBA #automation #evaluation #information retrieval: Practical evaluation of IR within automated classification systems (RD, JP, MB, RA), pp. 322–329.
CIKM-1999-GeffnerAAS #library #scalability #using: Browsing Large Digital Library Collections Using Classification Hierarchies (SG, DA, AEA, TRS), pp. 195–201.
CIKM-1999-HsuL #algorithm: Classification Algorithms for NETNEWS Articles (WLH, SDL), pp. 114–121.
CIKM-1999-LiY #probability #using: Text Classification Using ESC-based Stochastic Decision Lists (HL, KY), pp. 122–130.
CIKM-1999-MatsudaF #documentation #retrieval #web: Task-Oriented World Wide Web Retrieval by Document Type Classification (KM, TF), pp. 109–113.
ICML-1999-BlanzieriR #metric #nearest neighbour: A Minimum Risk Metric for Nearest Neighbor Classification (EB, FR), pp. 22–31.
ICML-1999-CardieMP #parsing: Combining Error-Driven Pruning and Classification for Partial Parsing (CC, SM, DRP), pp. 87–96.
ICML-1999-FanSZC #named: AdaCost: Misclassification Cost-Sensitive Boosting (WF, SJS, JZ, PKC), pp. 97–105.
ICML-1999-Joachims #using: Transductive Inference for Text Classification using Support Vector Machines (TJ), pp. 200–209.
ICML-1999-LangleyS #analysis #naive bayes: Tractable Average-Case Analysis of Naive Bayesian Classifiers (PL, SS), pp. 220–228.
ICML-1999-ScottM #re-engineering: Feature Engineering for Text Classification (SS, SM), pp. 379–388.
KDD-1999-AnkerstEEK #approach #interactive #visual notation: Visual Classification: An Interactive Approach to Decision Tree Construction (MA, CE, ME, HPK), pp. 392–396.
KDD-1999-BonchiGMP #detection: A Classification-Based Methodology for Planning Audit Strategies in Fraud Detection (FB, FG, GM, DP), pp. 175–184.
KDD-1999-Domingos #named: MetaCost: A General Method for Making Classifiers Cost-Sensitive (PMD), pp. 155–164.
KDD-1999-KellyHA #performance: The Impact of Changing Populations on Classifier Performance (MGK, DJH, NMA), pp. 367–371.
KDD-1999-LeshZO #mining #sequence: Mining Features for Sequence Classification (NL, MJZ, MO), pp. 342–346.
KDD-1999-MeretakisW #naive bayes #using: Extending Naïve Bayes Classifiers Using Long Itemsets (DM, BW), pp. 165–174.
KDD-T-1999-GehrkeLR: Classification and Regression: Money *can* Grow on Trees (JG, WYL, RR), pp. 1–73.
MLDM-1999-GiacintoR #automation #design #learning #multi: Automatic Design of Multiple Classifier Systems by Unsupervised Learning (GG, FR), pp. 131–143.
UML-1999-BernerGJ #modelling #object-oriented: A Classification of Stereotypes for Object-Oriented Modeling Languages (SB, MG, SJ), pp. 249–264.
UML-1999-MillerW #how #question: How Can Anything be Both a Classifier and a Package? (JM, RWB), pp. 584–597.
TOOLS-EUROPE-1999-MensWD #architecture #using: Declaratively Codifying Software Architectures Using Virtual Software Classifications (KM, RW, TD), pp. 33–45.
ICSE-1999-YakimovichBB #architecture #cost analysis #integration #off the shelf: Software Architecture Classification for Estimating the Cost of COTS Integration (DY, JMB, VRB), pp. 296–302.
DL-1998-HaasG: Page and Link Classifications: Connecting Diverse Resources (SWH, ESG), pp. 99–107.
ECDL-1998-LiuDSCHDC #documentation #library #visualisation: Visualizing Document Classification: A Search Aid for the Digital Library (YHL, PD, MS, JTC, MTH, MD, JDC), pp. 555–567.
SIGMOD-1998-ShintaniK #algorithm #mining #parallel: Parallel Mining Algorithms for Generalized Association Rules with Classification Hierarchy (TS, MK), pp. 25–36.
VLDB-1998-RastogiS #named: PUBLIC: A Decision Tree Classifier that Integrates Building and Pruning (RR, KS), pp. 404–415.
CSMR-1998-KawabeMUO #problem: Variable Classification Technique and Application to the Year 2000 Problem (KK, AM, SU, AO), pp. 44–51.
CIKM-1998-PapkaA #documentation #multi #using: Document Classification Using Multiword Features (RP, JA), pp. 124–131.
ICML-1998-Bay #multi #nearest neighbour #set: Combining Nearest Neighbor Classifiers Through Multiple Feature Subsets (SDB), pp. 37–45.
ICML-1998-BollackerG #architecture #reuse #scalability: A Supra-Classifier Architecture for Scalable Knowledge Reuse (KDB, JG), pp. 64–72.
ICML-1998-CristianiniSS #scalability: Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space (NC, JST, PS), pp. 109–117.
ICML-1998-FriedmanGL #network #parametricity: Bayesian Network Classification with Continuous Attributes: Getting the Best of Both Discretization and Parametric Fitting (NF, MG, TJL), pp. 179–187.
ICML-1998-MaronR #learning #multi: Multiple-Instance Learning for Natural Scene Classification (OM, ALR), pp. 341–349.
ICML-1998-McCallumN #learning: Employing EM and Pool-Based Active Learning for Text Classification (AM, KN), pp. 350–358.
ICML-1998-McCallumRMN: Improving Text Classification by Shrinkage in a Hierarchy of Classes (AM, RR, TMM, AYN), pp. 359–367.
ICML-1998-PrecupU #approximate #using: Classification Using Phi-Machines and Constructive Function Approximation (DP, PEU), pp. 439–444.
ICPR-1998-Aladjem #ml #network #recursion #reduction: Training of a ML neural network for classification via recursive reduction of the class separation (MA), pp. 450–452.
ICPR-1998-ArikiS #multi #using: Classification of TV sports news by DCT features using multiple subspace method (YA, YS), pp. 1488–1491.
ICPR-1998-BischofLP #robust: A robust subspace classifier (HB, AL, FP), pp. 114–116.
ICPR-1998-BreukelenD #network: Neural network initialization by combined classifiers (MvB, RPWD), pp. 215–218.
ICPR-1998-BulowS: Quaternionic gabor filters for local structure classification (TB, GS), pp. 808–810.
ICPR-1998-FrelicotL: A pretopology-based supervised pattern classifier (CF, FL), pp. 106–109.
ICPR-1998-GovindanDKP #analysis #component #independence: Independent component analysis applied to electrogram classification during atrial fibrillation (AG, GD, JK, JP), pp. 1662–1664.
ICPR-1998-HerouxDRT #automation #identification: Classification method study for automatic form class identification (PH, SD, AR, ÉT), pp. 926–928.
ICPR-1998-HojjatoleslamiK: Strategies for weighted combination of classifiers employing shared and distinct representations (AH, JK), pp. 338–340.
ICPR-1998-HuetP #fuzzy #image #multi: A multi-scale fuzzy classification by knn. Application to the interpretation of aerial images (FH, SP), pp. 96–98.
ICPR-1998-HuetP98a #fuzzy #image #multi #segmentation: Fusion of images after segmentation by various operators and interpretation by a multi-scale fuzzy classification (FH, SP), pp. 1843–1845.
ICPR-1998-IivarinenV #adaptation #fault: An adaptive texture and shape based defect classification (JI, AV), pp. 117–122.
ICPR-1998-KeeniNS #automation #estimation #generative #network #using: Automatic generation of initial weights and estimation of hidden units for pattern classification using neural networks (KK, KN, HS), pp. 1568–1571.
ICPR-1998-KeglKN #learning #network #parametricity: Radial basis function networks in nonparametric classification and function learning (BK, AK, HN), pp. 565–570.
ICPR-1998-Kraaijveld #comparison #parametricity: An experimental comparison of nonparametric classifiers for time-constrained classification tasks (MAK), pp. 428–435.
ICPR-1998-Kwok #problem: Support vector mixture for classification and regression problems (JTYK), pp. 255–258.
ICPR-1998-LamOX #learning: Application of Bayesian Ying-Yang criteria for selecting the number of hidden units with backpropagation learning to electrocardiogram classification (WKL, NO, LX), pp. 1686–1688.
ICPR-1998-LashkiaA #performance: Test feature classifiers: performance and application (VL, SA), pp. 341–343.
ICPR-1998-LiJ #documentation: Classification of text documents (YL, AKJ), pp. 1295–1297.
ICPR-1998-Mizutani #fault #learning: Discriminative learning for minimum error and minimum reject classification (HM), pp. 136–140.
ICPR-1998-NieuwoudtB #performance #using: Relative performance of correlation-based and feature-based classifiers of aircraft using radar range profiles (CN, ECB), pp. 1828–1832.
ICPR-1998-PalauS #approximate #nearest neighbour #performance: The labelled cell classifier: a fast approximation to k nearest neighbors (AMP, RRS), pp. 823–827.
ICPR-1998-Perner #analysis #image: Image analysis and classification of HEp-2 cells in fluorescent images (PP), pp. 1677–1679.
ICPR-1998-PrevostM #automation #multi #recognition: Automatic allograph selection and multiple expert classification for totally unconstrained handwritten character recognition (LP, MM), pp. 381–383.
ICPR-1998-QiTD #algorithm #feedback #search-based: Fingerprint classification system with feedback mechanism based on genetic algorithm (YQ, JT, RD), pp. 163–165.
ICPR-1998-RodriguezMNZMP: A two-stage classifier for broken and blurred digits in forms (CR, JM, MN, AZ, JIM, JMP), pp. 1101–1105.
ICPR-1998-SablatnigKZ #modelling #using: Hierarchical classification of paintings using face- and brush stroke models (RS, PK, EZ), pp. 172–174.
ICPR-1998-SatoY #learning #using: A formulation of learning vector quantization using a new misclassification measure (AS, KY), pp. 322–325.
ICPR-1998-ShahA #architecture #hybrid #performance #reasoning: A hybrid architecture for performance reasoning in classification systems (SS, JKA), pp. 326–330.
ICPR-1998-SukanyaTS #image #multi #using: Image classification using the surface-shape operator and multiscale features (PS, RT, MS), pp. 334–337.
ICPR-1998-SuriHS #automation #bound #polynomial: Automatic quadratic calibration for correction of pixel classification boundaries to an accuracy of 2.5 millimeters: an application in cardiac imaging (JSS, RMH, FHS), pp. 30–33.
ICPR-1998-UchidaKMT #integration #statistics: Fingerprint card classification with statistical feature integration (KU, TK, MM, TT), pp. 1833–1839.
ICPR-1998-WangLL #composition #markov #modelling #random #using: Texture classification using wavelet decomposition with Markov random field models (LW, JL, SZL), pp. 1613–1615.
ICPR-1998-ZhangFY #composition #modelling #recognition: A modular classification scheme with elastic net models for handwritten digit recognition (BZ, MF, HY), pp. 1859–1861.
KDD-1998-AlsabtiRS #dataset #named #scalability: CLOUDS: A Decision Tree Classifier for Large Datasets (KA, SR, VS), pp. 2–8.
KDD-1998-CohenH #using: Joins that Generalize: Text Classification Using WHIRL (WWC, HH), pp. 169–173.
KDD-1998-GraefeFC #database #on the #performance #scalability #sql #statistics: On the Efficient Gathering of Sufficient Statistics for Classification from Large SQL Databases (GG, UMF, SC), pp. 204–208.
KDD-1998-KeoghP #clustering #feedback #performance #representation: An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback (EJK, MJP), pp. 239–243.
KDD-1998-KohaviS: Targeting Business Users with Decision Table Classifiers (RK, DS), pp. 249–253.
KDD-1998-KontkanenMST #feature model #named: BAYDA: Software for Bayesian Classification and Feature Selection (PK, PM, TS, HT), pp. 254–258.
KDD-1998-LiuHM #mining: Integrating Classification and Association Rule Mining (BL, WH, YM), pp. 80–86.
KDD-1998-NakhaeizadehTL: Evaluating Usefulness for Dynamic Classification (GN, CT, CL), pp. 87–93.
KDD-1998-RidgewayMRO #naive bayes: Interpretable Boosted Naïve Bayes Classification (GR, DM, TR, JO), pp. 101–104.
KDD-1998-Rosset #comparison #evaluation #flexibility #named #performance #ranking: Ranking — Methods for Flexible Evaluation and Efficient Comparison of Classification Performance (SR), pp. 324–328.
KDD-1998-Stolfo #database #mining: Mining Databases with Different Schemas: Integrating Incompatible Classifiers (ALP, SJS), pp. 314–318.
SIGIR-1998-BakerM #clustering #word: Distributional Clustering of Words for Text Classification (LDB, AM), pp. 96–103.
SIGIR-1998-LinSCHKH #approach #documentation #internet #mining #semantics: Extracting Classification Knowledge of Internet Documents with Mining Term Associations: A Semantic Approach (SHL, CSS, MCC, JMH, MTK, YMH), pp. 241–249.
SIGIR-1998-RagasK #algorithm #corpus: Four Text Classification Algorithms Compared on a Dutch Corpus (HR, CHAK), pp. 369–370.
SAC-1998-HarandiR #distributed #problem: Classification and organizational issues in distributed problem solving (MTH, GR), pp. 65–69.
SAC-1998-Konstam #algorithm #programming #search-based #using: Group classification using a mix of genetic programming and genetic algorithms (AHK), pp. 308–312.
SAC-1998-LimaR: Maximum likelihood based classification for the microstructure of human sleep (JAL, ACR), pp. 60–64.
DAC-1998-XieB #finite #markov #performance: Efficient State Classification of Finite State Markov Chains (AX, PAB), pp. 605–610.
ICDAR-1997-AlimogluA #multi: Combining Multiple Representations and Classifiers for Pen-based Handwritten Digit Recognitio (FA, EA), pp. 637–640.
ICDAR-1997-AnisimovichRST #recognition #using: Using Combination of Structural, Feature and Raster Classifiers for Recognition of Handprinted Characters (KA, VR, AS, VT), pp. 881–885.
ICDAR-1997-ArikiT #recognition: Indexing and Classification of TV News Articles Based on Telop Recognition (YA, TT), pp. 422–427.
ICDAR-1997-BouletreauVSE #parametricity: Synthetic Parameters for Handwriting Classification (VB, NV, RS, HE), pp. 102–106.
ICDAR-1997-DingLS #using: Classification of Oriental and European Scripts by Using Characteristic Features (JD, LL, CYS), pp. 1023–1027.
ICDAR-1997-FrankeGKM #comparison #markov #modelling #polynomial #recognition: A Comparison of Gaussian Distribution and Polynomial Classifiers in a Hidden Markov Model Based System for the Recognition of Cursive Script (JF, JMG, AK, EM), pp. 515–518.
ICDAR-1997-Horiuchi: Pattern Classification Method by Integrating Interval Feature Values (TH), pp. 847–850.
ICDAR-1997-JunkerH #documentation #learning: Evaluating OCR and Non-OCR Text Representations for Learning Document Classifiers (MJ, RH), pp. 1060–1066.
ICDAR-1997-KangK #framework #multi #probability: Probabilistic Framework for Combining Multiple Classifiers at Abstract Level (HJK, JHK), pp. 870–874.
ICDAR-1997-KawataniS #component #design #difference #using: Complementary Classifier Design Using Difference Principal Components (TK, HS), pp. 875–880.
ICDAR-1997-KimSC #approach #multi #recognition: A systematic approach to classifier selection on combining multiple classifiers for handwritten digit recognition (JK, KS, KC), pp. 459–462.
ICDAR-1997-PrevostM #recognition: Static and Dynamic Classifier Fusion for Character Recognition (LP, MM), pp. 499–506.
ICDAR-1997-TeoS #hybrid: A Hybrid Classifier for Recognizing Handwritten Numerals (RYMT, RS), pp. 283–287.
ICDAR-1997-TsudaM #parametricity: A Nonparametric Density Model for Classification in a High Dimensional Space (KT, MM), pp. 1082–1087.
ICDAR-1997-WaizumiKSN #learning #using: High speed rough classification for handwritten characters using hierarchical learning vector quantization (YW, NK, KS, YN), pp. 23–27.
ICALP-1997-ManziniM #automaton #linear: A Complete and Efficiently Computable Topological Classification of D-dimensional Linear Cellular Automata over Zm (GM, LM), pp. 794–804.
ICML-1997-AskerM #case study #detection #re-engineering: Feature Engineering and Classifier Selection: A Case Study in Venusian Volcano Detection (LA, RM), pp. 3–11.
ICML-1997-Decatur #induction #learning: PAC Learning with Constant-Partition Classification Noise and Applications to Decision Tree Induction (SED), pp. 83–91.
ICML-1997-VilaltaR #induction #multi: Integrating Feature Construction with Multiple Classifiers in Decision Tree Induction (RV, LAR), pp. 394–402.
KDD-1997-AliMS #using: Partial Classification Using Association Rules (KA, SM, RS), pp. 115–118.
KDD-1997-Bayardo #mining: Brute-Force Mining of High-Confidence Classification Rules (RJBJ), pp. 123–126.
KDD-1997-Drucker #performance: Fast Committee Machines for Regression and Classification (HD), pp. 159–162.
KDD-1997-LiuHC #using: Using General Impressions to Analyze Discovered Classification Rules (BL, WH, SC), pp. 31–36.
KDD-1997-ProvostF #analysis #comparison #performance #visualisation: Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions (FJP, TF), pp. 43–48.
STOC-1997-KhannaSW #constraints #problem: A Complete Classification of the Approximability of Maximization Problems Derived from Boolean Constraint Satisfaction (SK, MS, DPW), pp. 11–20.
CADE-1997-Nivelle #order: A Classification of Non-liftable Orders for Resolution (HdN), pp. 336–350.
VLDB-1996-ShaferAM #data mining #mining #named #parallel #scalability: SPRINT: A Scalable Parallel Classifier for Data Mining (JCS, RA, MM), pp. 544–555.
ICSM-1996-OwensWG #fault #using: Software Error Classification using Purify (HDO, BFW, MJG), pp. 104–113.
AKDDM-1996-CheesemanS: Bayesian Classification (AutoClass): Theory and Results (PC, JS), pp. 153–180.
ICML-1996-AkkusG #nearest neighbour: K Nearest Neighbor Classification on Feature Projections (AA, HAG), pp. 12–19.
ICML-1996-DomingosP #independence: Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier (PMD, MJP), pp. 105–112.
ICML-1996-GreinerGR #learning: Learning Active Classifiers (RG, AJG, DR), pp. 207–215.
ICML-1996-OkamotoY #analysis #nearest neighbour: Theoretical Analysis of the Nearest Neighbor Classifier in Noisy Domains (SO, NY), pp. 355–363.
ICML-1996-SinghP #learning #network #performance: Efficient Learning of Selective Bayesian Network Classifiers (MS, GMP), pp. 453–461.
ICPR-1996-AchermannB #identification: Combination of face classifiers for person identification (BA, HB), pp. 416–420.
ICPR-1996-BandyopadhyayMP: GA-based pattern classification: theoretical and experimental studies (SB, CAM, SKP), pp. 758–762.
ICPR-1996-Bobrowski #learning #set: Piecewise-linear classifiers, formal neurons and separability of the learning sets (LB), pp. 224–228.
ICPR-1996-BonifaziMNP #image #industrial #recognition: The classification of industrial sand-ores by image recognition methods (GB, PM, LN, GP), pp. 174–179.
ICPR-1996-ChangL: Classification with nonexclusive patterns (IC, MHL), pp. 116–120.
ICPR-1996-ChenLC #analysis #sequence #using: Handwritten Chinese character analysis and preclassification using stroke structural sequence (ZC, CWL, RHC), pp. 89–93.
ICPR-1996-ChetverikovLKH #using: Zone classification using texture features (DC, JL, JK, RMH), pp. 676–680.
ICPR-1996-CohenDE #image: Computerized classification of color textured perthite images (BC, ID, ME), pp. 601–605.
ICPR-1996-CortijoB #automation #estimation #image #multi #parametricity: Automatic estimation of the LVQ-1 parameters. Applications to multispectral image classification (FJC, NPdlB), pp. 346–350.
ICPR-1996-DiasBD #identification #using: Results of the use of Bayesian classifiers for identification of breast cancer cell nuclei (ÂVD, FB, MRD), pp. 508–512.
ICPR-1996-DoeringW #composition #cost analysis #network #set: Feedforward neural networks for Bayes-optimal classification: investigations into the influence of the composition of the training set on the cost function (AD, HW), pp. 219–223.
ICPR-1996-FerrariBG #array: A VLSI array processor accelerator for k-NN classification (AF, MB, RG), pp. 723–727.
ICPR-1996-GonzalezC #functional #markov #random: The Markov random fields in functional neighbors as a texture model: applications in texture classification (AMG, DC), pp. 815–819.
ICPR-1996-HepplewhiteS #pattern matching #pattern recognition #recognition #using: Texture classification using n-tuple pattern recognition (LH, TJS), pp. 159–163.
ICPR-1996-HoekstraD #on the: On the nonlinearity of pattern classifiers (AH, RPWD), pp. 271–275.
ICPR-1996-HoK #complexity: Building projectable classifiers of arbitrary complexity (TKH, EMK), pp. 880–885.
ICPR-1996-HolmstromKLO #network #statistics: Neural network and statistical perspectives of classification (LH, PK, JL, EO), pp. 286–290.
ICPR-1996-HuangLSSSLTH #approach #nearest neighbour #prototype: A simulated annealing approach to construct optimized prototypes for nearest-neighbor classification (YSH, KL, CYS, AJS, IIS, MCL, RYT, PKH), pp. 483–487.
ICPR-1996-HwangB #network #performance #recognition: An efficient method to construct a radial basis function neural network classifier and its application to unconstrained handwritten digit recognition (YSH, SYB), pp. 640–644.
ICPR-1996-JozwikCCS #fuzzy: A 1-NN preclassifier for fuzzy k-NN rule (AJ, LC, WC, MS), pp. 234–238.
ICPR-1996-KalviainenBPK #random: Mixed pixel classification with the randomized Hough transform (HK, PB, MP, JK), pp. 576–580.
ICPR-1996-KauppinenS #fault: The effect of illumination variations on color-based wood defect classification (HK, OS), pp. 828–832.
ICPR-1996-KindratenkoE #fourier #using: Classification of irregularly shaped micro-objects using complex Fourier descriptors (VVK, PJMVE), pp. 285–289.
ICPR-1996-KitamotoT #image #probability: A stochastic model of mixels and image classification (AK, MT), pp. 745–749.
ICPR-1996-KittlerHD: Combining classifiers (JK, MH, RPWD), pp. 897–901.
ICPR-1996-KrzyzakL #complexity #convergence #network #parametricity: Radial basis function networks and nonparametric classification: complexity regularization and rates of convergence (AK, TL), pp. 650–653.
ICPR-1996-KudoS #using: Selection of classifiers based on the MDL principle using the VC dimension (MK, MS), pp. 886–890.
ICPR-1996-LaferteHP #algorithm #image #multi: A multiresolution EM algorithm for unsupervised image classification (JML, FH, PP), pp. 849–853.
ICPR-1996-LernerGADR #feature model #network: Feature extraction by neural network nonlinear mapping for pattern classification (BL, HG, MA, ID, YR), pp. 320–324.
ICPR-1996-LiuL #approach #effectiveness #performance #using: An efficient and effective texture classification approach using a new notion in wavelet theory (JFL, JCML), pp. 820–824.
ICPR-1996-MaioM #approach: A structural approach to fingerprint classification (DM, DM), pp. 578–585.
ICPR-1996-MurshedBS #approach #detection #fuzzy #problem: A fuzzy ARTMAP-based classification system for detecting cancerous cells, based on the one-class problem approach (NAM, FB, RS), pp. 478–482.
ICPR-1996-PeuraVK #approach: A new approach to land-based cloud classification (MP, AV, PK), pp. 143–147.
ICPR-1996-PietikainenNMO: Accurate color discrimination with classification based on feature distributions (MP, SN, EM, TO), pp. 833–838.
ICPR-1996-Raudys #design #linear: Linear classifiers in perceptron design (SR), pp. 763–767.
ICPR-1996-RaudysD #empirical #fault: Expected error of minimum empirical error and maximal margin classifiers (SR, VD), pp. 875–879.
ICPR-1996-RoliSB #image #multi #network: Classification of multisensor remote-sensing images by multiple structured neural networks (FR, SBS, LB), pp. 180–184.
ICPR-1996-Skubalska-RafajlowiczK #metric #performance #using: Fast k-NN classification rule using metric on space-filling curves (ESR, AK), pp. 121–125.
ICPR-1996-SkurichinaD: Stabilizing classifiers for very small sample sizes (MS, RPWD), pp. 891–896.
ICPR-1996-Solberg #analysis #flexibility: Texture fusion and classification based on flexible discriminant analysis (AHSS), pp. 596–600.
ICPR-1996-StockerRLE #distributed #incremental: Incremental distributed classifier building (ES, AR, YL, AE), pp. 128–132.
ICPR-1996-SzeL #algorithm #bound #branch: Branch and bound algorithm for the Bayes classifier (LS, CHL), pp. 705–709.
ICPR-1996-TingL #string #using: Business form classification using strings (AT, MKHL), pp. 690–694.
ICPR-1996-TumerG #fault: Estimating the Bayes error rate through classifier combining (KT, JG), pp. 695–699.
ICPR-1996-VriesengaS #linear #modelling: Neural modeling of piecewise linear classifiers (MV, JS), pp. 281–285.
ICPR-1996-WouwerSD #analysis #speech: Wavelet-FILVQ classifier for speech analysis (GVdW, PS, DVD), pp. 214–218.
ICPR-1996-Yoshii #architecture: Pyramid architecture classification tree (HY), pp. 310–314.
ICPR-1996-ZhangHG #image #knowledge-based #monitoring: Knowledge-based classification of CZCS images and monitoring of red tides off the west Florida shelf (MZ, LOH, DBG), pp. 452–456.
KDD-1996-Kohavi #hybrid #scalability: Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid (RK), pp. 202–207.
KDD-1996-Sahami #dependence #learning: Learning Limited Dependence Bayesian Classifiers (MS), pp. 335–338.
KDD-1996-ShanZHC #database #set #using: Discovering Classification Knowledge in Databases Using Rough Sets (NS, WZ, HJH, NC), pp. 271–274.
KR-1996-JonssonDB #algebra #subclass: Tractable Subclasses of the Point-Interval Algebra: A Complete Classification (PJ, TD, CB), pp. 352–363.
SIGIR-1996-LarkeyC #categorisation: Combining Classifiers in Text Categorization (LSL, WBC), pp. 289–297.
SIGIR-1996-LewisSCP #algorithm #linear: Training Algorithms for Linear Text Classifiers (DDL, RES, JPC, RP), pp. 298–306.
SAC-1996-HarangsriSN #multi #optimisation #query #using: Query optimisation in multidatabase systems using query classification (BH, JS, AHHN), pp. 173–177.
SAC-1996-HasemiPAHP #approach #search-based: A rough-genetic approach for classification of complex data (RH, BAP, RBA, WGH, MGP), pp. 282–288.
PDP-1996-RiedlR #algorithm: Classification of Load Distribution Algorithms (RR, LR), pp. 404–413.
ICDAR-v1-1995-BunkeL #documentation #parsing #using: Classification and postprocessing of documents using an error-correcting parser (HB, RL), pp. 222–226.
ICDAR-v1-1995-CaoSA #fuzzy: Fusion of classifiers with fuzzy integrals (JC, MS, MA), pp. 108–111.
ICDAR-v1-1995-HongLHS #design #nearest neighbour #recognition: The design of a nearest-neighbor classifier and its use for Japanese character recognition (TH, SWKL, JJH, SNS), pp. 270–273.
ICDAR-v1-1995-KimD #distance #network #recognition #using: Off-line Recognition of Korean Scripts Using Distance Matching and Neural Network Classifiers (SHK, JID), pp. 34–37.
ICDAR-v1-1995-LeeS #approach #formal method #network: A theory of classifier combination: the neural network approach (DSL, SNS), pp. 42–45.
ICDAR-v1-1995-SabourinG #approach #evaluation #multi #verification: An extended-shadow-code based approach for off-line signature verification. II. Evaluation of several multi-classifier combination strategies (RS, GG), pp. 197–201.
ICDAR-v1-1995-StrathyS #multi #network: A two-stage multi-network OCR system with a soft pre-classifier and a network selector (NWS, CYS), pp. 78–81.
ICDAR-v1-1995-Summers #documentation: Near-wordless document structure classification (KMS), pp. 462–465.
ICDAR-v1-1995-TingLHC: A syntactic business form classifier (AT, MKHL, SCH, KYC), pp. 301–304.
ICDAR-v1-1995-UtschickNKSN #evaluation #feature model #network: The evaluation of feature extraction criteria applied to neural network classifiers (WU, PN, CK, AS, JAN), pp. 315–318.
ICDAR-v2-1995-AntonacopoulosR #representation #using: Representation and classification of complex-shaped printed regions using white tiles (AA, RTR), pp. 1132–1135.
ICDAR-v2-1995-DengelD #approach #clustering #documentation #machine learning: Clustering and classification of document structure-a machine learning approach (AD, FD), pp. 587–591.
ICDAR-v2-1995-DrouhardSG #case study #comparative #nearest neighbour #network #using #verification: Comparative study of the k nearest neighbour, threshold and neural network classifiers for handwritten signature verification using an enhanced directional PDF (JPD, RS, MG), pp. 807–810.
ICDAR-v2-1995-JungN #design: Joint feature and classifier design for OCR (DMJ, GN), pp. 1115–1118.
ICDAR-v2-1995-MadhvanathG #recognition #word: Serial classifier combination for handwritten word recognition (SM, VG), pp. 911–914.
ICDAR-v2-1995-MatsunagaK #case study #learning #statistics: An experimental study of learning curves for statistical pattern classifiers (TM, HK), pp. 1103–1106.
ICDAR-v2-1995-SauvolaP #analysis #feature model #performance #segmentation #using: Page segmentation and classification using fast feature extraction and connectivity analysis (JJS, MP), pp. 1127–1131.
ICDAR-v2-1995-SivaramakrishnanPHSH #documentation #generative #using: Zone classification in a document using the method of feature vector generation (RS, ITP, JH, SS, RMH), pp. 541–544.
ICDAR-v2-1995-TaylorLN #composition #documentation #functional: Classification and functional decomposition of business documents (SLT, ML, RWN), pp. 563–566.
ICDAR-v2-1995-WangW #multi #recognition: A multi-layer classifier for recognition of unconstrained handwritten numerals (GEW, JFW), pp. 849–852.
ICDAR-v2-1995-ZhouHL #recognition: A method of Jia Gu Wen recognition based on a two-level classification (XLZ, XCH, FL), pp. 833–836.
VLDB-1995-TreschPL #documentation: Type Classification of Semi-Structured Documents (MT, NP, AL), pp. 263–274.
WCRE-1995-LakhotiaG #evaluation #towards: Toward Experimental Evaluation of Subsystem Classification Recovery Techniques (AL, JMG), pp. 262–269.
CIKM-1995-TreschL #documentation: An Extensible Classifier for Semi-Structured Documents (MT, AL), pp. 226–233.
ICML-1995-DaganE #probability: Committee-Based Sampling For Training Probabilistic Classifiers (ID, SPE), pp. 150–157.
ICML-1995-Drakopoulos #bound #fault #nearest neighbour: Bounds on the Classification Error of the Nearest Neighbor Rule (JAD), pp. 203–208.
ICML-1995-Lubinsky #consistency #performance #using: Increasing the Performance and Consistency of Classification Trees by Using the Accuracy Criterion at the Leaves (DJL), pp. 371–377.
ICML-1995-SinghP #algorithm #comparison #induction: A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers (MS, GMP), pp. 497–505.
ICML-1995-SmythGF #estimation #kernel #using: Retrofitting Decision Tree Classifiers Using Kernel Density Estimation (PS, AGG, UMF), pp. 506–514.
KDD-1995-HastieT #adaptation #nearest neighbour: Discriminant Adaptive Nearest Neighbor Classification (TH, RT), pp. 142–149.
KDD-1995-Pazzani #approach: An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers (MJP), pp. 228–233.
SEKE-1995-Borstler #feature model #reuse: Feature-Oriented Classification for Software Reuse (JB), pp. 204–211.
SIGIR-1995-Lewis #optimisation: Evaluating and Optimizing Autonomous Text Classification Systems (DDL), pp. 246–254.
SIGIR-1995-Riloff #difference #word: Little Words Can Make a Big Difference for Text Classification (ER), pp. 130–136.
SIGIR-1995-SchutzeHP #comparison #documentation #problem: A Comparison of Classifiers and Document Representations for the Routing Problem (HS, DAH, JOP), pp. 229–237.
AdaEurope-1995-Kempe #ada #data type #semistructured data: Heterogeneous Data Structures and Cross-Classification of Objects with Ada95 (MK), pp. 71–80.
RE-1995-Zave #requirements #research: Classification of research efforts in requirements engineering (PZ), pp. 214–216.
KBSE-1995-PenixBA #component #retrieval #reuse #semantics #using: Classification and Retrieval of Reusable Components Using Semantic Features (JP, PB, PA), pp. 131–138.
SAC-1995-HalgamugeBG #algorithm #comparison #generative #heuristic #rule-based #search-based: Comparison of a heuristic method with a genetic algorithm for generation of compact rule based classifiers (SKH, AB, MG), pp. 580–585.
SAC-1995-NauckK #approach: NEFCLASSmdash;a neuro-fuzzy approach for the classification of data (DN, RK), pp. 461–465.
SAC-1995-Stegmaier-StraccaT #detection #fuzzy #using: Cough detection using fuzzy classification (PASS, NNTG), pp. 440–444.
SAC-1995-Tschichold-Gurman #fuzzy #generative #incremental #learning #using: Generation and improvement of fuzzy classifiers with incremental learning using fuzzy RuleNet (NNTG), pp. 466–470.
CAiSE-1994-Odberg #database #evolution #flexibility #object-oriented: Category Classes: Flexible Classification and Evolution in Object-Oriented Databases (EO), pp. 406–420.
CIKM-1994-HeinleinKD #guidelines #representation: Representation of Medical Guidelines on Top of a Classification-Based System (CH, KK, PD), pp. 415–422.
CIKM-1994-RoseG #database: Hierarchical Classification as an Aid to Database and Hit-List Browsing (JRR, JG), pp. 408–414.
CIKM-1994-Rundensteiner #algorithm #object-oriented: A Classification Algorithm for Supporting Object-Oriented Views (EAR), pp. 18–25.
ICML-1994-PazzaniMMAHB: Reducing Misclassification Costs (MJP, CJM, PMM, KMA, TH, CB), pp. 217–225.
SIGIR-1994-Hoch #analysis #documentation #information retrieval #using: Using IR Techniques for Text Classification in Document Analysis (RH), pp. 31–40.
SIGIR-1994-LewisG #algorithm: A Sequential Algorithm for Training Text Classifiers (DDL, WAG), pp. 3–12.
SAC-1994-AleshunasCB: Classification characteristics of SOM and ART2 (JJA, DCSC, WEB), pp. 297–302.
SAC-1994-FlachsbartBCH #algorithm #using: Using the ID3 symbolic classification algorithm to reduce data density (BF, WEB, DCSC, JH), pp. 292–296.
SAC-1994-GentherG #automation #clustering #fuzzy #generative #using: Automatic generation of a fuzzy classification system using fuzzy clustering methods (HG, MG), pp. 180–183.
SAC-1994-Konstam #algorithm #search-based #using: N-group classification using genetic algorithms (AHK), pp. 212–216.
SAC-1994-RitschelPG #multi #rating: Rating of pattern classifications in multi-layer perceptrons: theoretical background and practical results (WR, TP, RG), pp. 142–144.
SAC-1994-Sen: Representational effects in a simple classifier system (SS), pp. 206–211.
SAC-1994-Tschichold-Gurman #fuzzy #network: Fuzzy RuleNet: an artificial neural network model for fuzzy classification (NNTG), pp. 145–149.
EDAC-1994-RobertGMT #design #geometry #realtime: Design of a Real Time Geometric Classifier (MR, PG, JM, ST), p. 656.
ICDAR-1993-BayerK #segmentation: Cut classification for segmentation (TAB, UK), pp. 565–568.
ICDAR-1993-CaesarGM93a #adaptation #scalability #set: Utilization of large disordered sample sets for classifier adaptation in complex domains (TC, JMG, EM), pp. 790–793.
ICDAR-1993-DuneauD #recognition: An improved classification for cursive script recognition (LD, BD), pp. 842–845.
ICDAR-1993-FrankeO #detection #statistics: Writing style detection by statistical combination of classifiers in form reader applications (JF, MFO), pp. 581–584.
ICDAR-1993-HaoWN #analysis #approach #documentation #layout #segmentation: Nested segmentation: an approach for layout analysis in document classification (XH, JTLW, PAN), pp. 319–322.
ICDAR-1993-HuangS #metric #multi: Combination of multiple classifiers with measurement values (YSH, CYS), pp. 598–601.
ICDAR-1993-ImadeTW #documentation #image #network #segmentation #using: Segmentation and classification for mixed text/image documents using neural network (SI, ST, TW), pp. 930–934.
ICDAR-1993-IwaneYI #analysis #approach #documentation #functional #image #layout: A functional classification approach to layout analysis of document images (KI, MY, OI), pp. 778–781.
ICDAR-1993-IwataM #algorithm: A color classification algorithm (KI, GM), pp. 726–729.
ICDAR-1993-NakajimaM #modelling #recognition: A model-based classifier in a scheme of recognition filter (YN, SM), pp. 68–71.
ICDAR-1993-PlessisSHMLDM #multi #recognition #word: A multi-classifier combination strategy for the recognition of handwritten cursive words (BP, AS, LH, EM, EL, OD, JVM), pp. 642–645.
ICDAR-1993-SabourinMTN #recognition: Classifier combination for hand-printed digit recognition (MS, AM, DST, GN), pp. 163–166.
ICDAR-1993-Yan #design #implementation #nearest neighbour #recognition: Design and implementation of optimized nearest neighbor classifiers for handwritten digit recognition (HY), pp. 10–13.
ICDAR-1993-Yan93a #image #nearest neighbour #segmentation #using: Color map image segmentation using optimized nearest neighbor classifiers (HY), pp. 111–114.
ICDAR-1993-ZidouriCS #documentation #image: Classification of compound document image patterns by MCR stroke index (ABCZ, SC, MS), pp. 753–756.
CIKM-1993-EickJ #algorithm #learning #search-based: Learning Bayesian Classification Rules through Genetic Algorithms (CFE, DJ), pp. 305–313.
CIKM-1993-Riloff #using: Using Cases to Represent Context for Text Classification (ER), pp. 105–113.
SEKE-1993-LaiY #grid #multi #reuse #usability: Multi-Layer Repertory Grid Classification for Increasing Software Reusability (STL, CCY), pp. 252–254.
SEKE-1993-Porter #component #predict: Developing and Analyzing Classification Rules for Predicting Faulty Software Components (AAP), pp. 453–461.
RE-1993-BickertonS #requirements: The classification of requirements engineering methods (MJB, JS), pp. 182–186.
ICSE-1993-Zelkowitz #using: Use of an Environment Classification Model (MVZ), pp. 348–357.
VLDB-1992-AgrawalGIIS #database #mining: An Interval Classifier for Database Mining Applications (RA, SPG, TI, BRI, ANS), pp. 560–573.
ML-1992-HunterHS #performance: Efficient Classification of Massive, Unsegmented Datastreams (LH, NLH, DJS), pp. 224–232.
ML-1992-Venturini #named: AGIL: Solving the Exploration Versus Exploration Dilemma in a single Classifier System Applied to Simulated Robotics (GV), pp. 458–463.
SIGIR-1992-BlossevilleHMP #analysis #automation #documentation #natural language #statistics: Automatic Document Classification: Natural Language Processing, Statistical Analysis, and Expert System Techniques used together (MJB, GH, MGM, NP), pp. 51–58.
OOPSLA-1992-Yelland #smalltalk: Experimental Classification Facilities for Smalltalk (PMY), pp. 235–246.
TOOLS-EUROPE-1992-KarlssonST #component #object-oriented #reuse: Classification of Object-Oriented Components for Reuse (EAK, LSS, ET), pp. 21–31.
KDD-1991-ChanW #database #statistics: Statistical Technique for Extracting Classificatory Knowledge from Databases (KCCC, AKCW), pp. 107–124.
KDD-1991-WuSO #heuristic #integration: Integration of Heuristic and Bayesian Approaches in a Pattern-Classification System (QW, PS, AO), pp. 249–260.
ML-1991-BelyaevF: Noise-Resistant Classification (LVB, LPF), pp. 581–585.
ML-1991-CrawfordFAT #information retrieval: Classification Trees for Information Retrieval (SLC, RMF, LAA, RMT), pp. 245–249.
POPL-1991-LandiR #alias #pointer #problem: Pointer-Induced Aliasing: A Problem Classification (WL, BGR), pp. 93–103.
ESEC-1991-SelbyM #analysis #metric: Metric-Driven Classification Analysis (RWS, RKM), pp. 290–307.
SEKE-1990-EichmannA #design: Design of a Lattice-Based Faceted Classification System (DE, JA), pp. 90–97.
ICSE-1990-Diaz #implementation #reuse: Implementing Faceted Classification for Software Reuse (RPD), pp. 300–304.
LICS-1990-Jung: The Classification of Continuous Domains (AJ), pp. 35–40.
CAiSE-1989-HernbackL #analysis #automation #framework #implementation #tool support: A Framework for Use and Classification of CASE Tools in Systems Analysis and a Strategy for Implementation (JH, IL).
CAiSE-1989-Nilsson #development #information management: Information Systems Development: A Frame Of Reference and Classifications (AGN).
ML-1989-Buntine #learning #using: Learning Classification Rules Using Bayes (WLB), pp. 94–98.
ML-1989-HilliardLRP #approach #hybrid #learning #problem #scheduling: Learning Decision Rules for scheduling Problems: A Classifier Hybrid Approach (MRH, GEL, GR, MRP), pp. 188–190.
SIGIR-1989-Kwasnik #documentation #how: How a Personal Document’s Intended Use or Purpose Affects its Classification in an Office (BHK), pp. 207–210.
SIGMOD-1988-YounHH #database #deduction #recursion: Classification of Recursive Formulas in Deductive Databases (CY, LJH, JH), pp. 320–328.
ML-1988-CheesemanKSSTF #named: AutoClass: A Bayesian Classification System (PC, JK, MS, JS, WT, DF), pp. 54–64.
ML-1988-DavisY: Classifier Systems with Hamming Weights (LD, DKY), pp. 162–173.
ML-1988-Quinlan #comparison #empirical #search-based: An Empirical Comparison of Genetic and Decision-Tree Classifiers (JRQ), pp. 135–141.
ML-1988-Robertson: Population Size in classifier Systems (GGR), pp. 142–152.
ML-1988-TanE #network #using: Using Weighted Networks to Represent Classification Knowledge in Noisy Domains (MT, LJE), pp. 121–134.
ECOOP-1988-Knudsen #multi: Name Collision in Multiple Classification Hierarchies (JLK), pp. 93–109.
JICSCP-1988-AptB88 #modelling #source code: Arithmetic Classification of Perfect Models of Stratified Programs (KRA, HAB), pp. 765–779.
ECOOP-1987-KristensenMMN #inheritance: Classification of Actions, or Inheritance also for Methods (BBK, OLM, BMP, KN), pp. 98–107.
ICALP-1986-AverbuchWG #algorithm #polynomial: Classification of all the Minimal Bilinear Algorithms for Computing the Coefficients of the Product of Two Polynomials Modulo a Polynomial (AA, SW, ZG), pp. 31–39.
CADE-1986-Walther #problem #unification: A Classification of Many-Sorted Unification Problems (CW), pp. 525–537.
VLDB-1984-Woehl #automation #database #documentation #prolog #relational: Automatic Classification of Office Documents by Coupling Relational Data Bases and PROLOG Expert Systems (KW), pp. 529–532.
CADE-1982-SiekmannS #equation #unification: Universal Unification and a Classification of Equational Theories (JHS, PS), pp. 369–389.
SIGIR-1981-Fraenkel #documentation #problem: Document Classification, Indexing and Abstracting May be Inherently Difficult Problems (ASF), pp. 77–82.
VLDB-1978-Ashany #analysis #database #matrix #retrieval #scalability: Application of Sparse Matrix Techniques to Search, Retrieval, Classification and Relationship Analysis in Large Data Base Systems — SPARCOM (RA), pp. 499–516.
DAC-1978-Harvel #effectiveness: Classification of PCB types for cost effective solutions (JTH), pp. 444–445.
SIGIR-1971-Jackson: Optimal Classification and Its Consequences (DMJ), pp. 217–224.
STOC-1971-Machtey #recursion: Classification of Computable Functions by Primitive Recursive Classes (MM), pp. 251–257.