Stem classifi$ (all stems)

727 papers:

CASE-2015-BrisimiAZCP #detection

Sensing and classifying roadway obstacles: The street bump anomaly detection and decision support system (TSB, SA, YZ, CGC, ICP), pp. 1288–1293.

DAC-2015-VenkataramaniRL #classification #energy #machine learning

Scalable-effort classifiers for energy-efficient machine learning (SV, AR, JL, MS), p. 6.

ICSME-2015-PanichellaSGVCG #evolution #how #maintenance

How can i improve my app? Classifying user reviews for software maintenance and evolution (SP, ADS, EG, CAV, GC, HCG), pp. 281–290.

MSR-2015-DuijnKB #quality #stack overflow

Quality Questions Need Quality Code: Classifying Code Fragments on Stack Overflow (MD, AK, AB), pp. 410–413.

MSR-2015-OhiraKYYMLFHIM #classification #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-2015-KayPK #bibliography #classification #evaluation #how

How Good is 85%?: A Survey Tool to Connect Classifier Evaluation to Acceptability of Accuracy (MK, SNP, JAK), pp. 347–356.

CSCW-2015-ChengB #classification #hybrid #machine learning #named

Flock: Hybrid Crowd-Machine Learning Classifiers (JC, MSB), pp. 600–611.

LCT-2015-Sein-EchaluceBG #education #information management #social #using

A Knowledge Management System to Classify Social Educational Resources Within a Subject Using Teamwork Techniques (MLSE, ÁFB, FJGP, MÁCG), pp. 510–519.

ICML-2015-OsadchyHK #classification

K-hyperplane Hinge-Minimax Classifier (MO, TH, DK), pp. 1558–1566.

KDD-2015-BifetMRHP #big data #classification #data type #evaluation #online #performance

Efficient Online Evaluation of Big Data Stream Classifiers (AB, GDFM, JR, GH, BP), pp. 59–68.

KDD-2015-ChuHTLL #classification #linear #parametricity

Warm Start for Parameter Selection of Linear Classifiers (BYC, CHH, CHT, CYL, CJL), pp. 149–158.

MLDM-2015-CostaFK #multi #using

Classifying Grasslands and Cultivated Pastures in the Brazilian Cerrado Using Support Vector Machines, Multilayer Perceptrons and Autoencoders (WC, LMGF, TSK), pp. 187–198.

MLDM-2015-DavidsenSP #classification #fuzzy #search-based

Local and Global Genetic Fuzzy Pattern Classifiers (SAD, ES, MP), pp. 55–69.

SEKE-2015-AdamEA #approach #design

An approach for classifying design artifacts (SA, GEB, AA), pp. 164–167.

AMT-2015-HilkenBGV #development #modelling #using

Iterative Development of Transformation Models by Using Classifying Terms (FH, LB, MG, AV), pp. 1–6.

MoDELS-2015-GogollaVBH #model transformation #testing

Employing classifying terms for testing model transformations (MG, AV, LB, FH), pp. 312–321.

SAC-2015-BerardiEF015a #case study #design #industrial

Classifying websites by industry sector: a study in feature design (GB, AE, TF, FS), pp. 1053–1059.

SAC-2015-BurkhardtK #classification #multi #on the

On the spectrum between binary relevance and classifier chains in multi-label classification (SB, SK), pp. 885–892.

SAC-2015-GomesBE #classification #data type #learning

Pairwise combination of classifiers for ensemble learning on data streams (HMG, JPB, FE), pp. 941–946.

SAC-2015-PaivaBSIJ #behaviour #learning #recommendation #student

Improving pedagogical recommendations by classifying students according to their interactional behavior in a gamified learning environment (ROAP, IIB, APdS, SI, PAJ), pp. 233–238.

ICSE-v1-2015-YuBC #approach #fault #multi #testing

Does the Failing Test Execute a Single or Multiple Faults? An Approach to Classifying Failing Tests (ZY, CB, KYC), pp. 924–935.

ICST-2015-LelliBB #fault #user interface

Classifying and Qualifying GUI Defects (VL, AB, BB), pp. 1–10.

DAC-2014-AlbalawiLL #algorithm #classification #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.

DocEng-2014-WilliamsCG #ranking

Classifying and ranking search engine results as potential sources of plagiarism (KW, HHC, CLG), pp. 97–106.

VLDB-2014-YuYWLC #big data #classification #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.

ICPC-2014-GuptaS #program analysis #quality

A semiautomated method for classifying program analysis rules into a quality model (SG, HKS), pp. 266–270.

MSR-2014-MertenMBP #natural language #semistructured data

Classifying unstructured data into natural language text and technical information (TM, BM, SB, BP), pp. 300–303.

CHI-2014-SoloveyZPRM #performance #using

Classifying driver workload using physiological and driving performance data: two field studies (ETS, MZ, EAGP, BR, BM), pp. 4057–4066.

VISSOFT-2014-DanielWSSL #classification #dependence #named #visualisation

Polyptychon: A Hierarchically-Constrained Classified Dependencies Visualization (DTD, EW, KS, MS, PL), pp. 83–86.

CIKM-2014-GrbovicHKM #category theory #email #how

How Many Folders Do You Really Need?: Classifying Email into a Handful of Categories (MG, GH, ZSK, YM), pp. 869–878.

CIKM-2014-LiZLW #classification #probability

Probabilistic Classifier Chain Inference via Gibbs Sampling (LL, LZ, GL, HW), pp. 1855–1858.

ECIR-2014-McDonaldMOG #bibliography #classification #perspective #towards

Towards a Classifier for Digital Sensitivity Review (GM, CM, IO, TG), pp. 500–506.

ICML-c2-2014-BaiLS #classification #framework #online

A Bayesian Framework for Online Classifier Ensemble (QB, HL, SS), pp. 1584–1592.

ICML-c2-2014-EbanMG #classification

Discrete Chebyshev Classifiers (EE, EM, AG), pp. 1233–1241.

ICML-c2-2014-SinglaBBKK #education

Near-Optimally Teaching the Crowd to Classify (AS, IB, GB, AK, AK), pp. 154–162.

ICML-c2-2014-SunIM #classification #learning #linear

Learning Mixtures of Linear Classifiers (YS, SI, AM), pp. 721–729.

ICPR-2014-AlvaroSB #network

Offline Features for Classifying Handwritten Math Symbols with Recurrent Neural Networks (FA, JAS, JMB), pp. 2944–2949.

ICPR-2014-BagheriHGE #classification #framework #multi #recognition

A Framework of Multi-classifier Fusion for Human Action Recognition (MAB, GH, QG, SE), pp. 1260–1265.

ICPR-2014-BhattacharyaGC #classification #estimation

Test Point Specific k Estimation for kNN Classifier (GB, KG, ASC), pp. 1478–1483.

ICPR-2014-BouillonA #classification #evolution #gesture #learning #online

Supervision Strategies for the Online Learning of an Evolving Classifier for Gesture Commands (MB, ÉA), pp. 2029–2034.

ICPR-2014-Cevikalp #classification

2-Sided Best Fitting Hyperplane Classifier (HC), pp. 226–231.

ICPR-2014-ColonnaCN #approach #distributed

A Distributed Approach for Classifying Anuran Species Based on Their Calls (JGC, MC, EFN), pp. 1242–1247.

ICPR-2014-DuHZWD #case study #classification #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-Filippone #classification #process #pseudo

Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC (MF), pp. 614–619.

ICPR-2014-HadjadjiCG #classification #multi

Multiple One-Class Classifier Combination for Multi-class Classification (BH, YC, YG), pp. 2832–2837.

ICPR-2014-HobsonLPVW #anti #benchmark #framework #image #metric

Classifying Anti-nuclear Antibodies HEp-2 Images: A Benchmarking Platform (PH, BCL, GP, MV, AW), pp. 3233–3238.

ICPR-2014-KrawczykWC #classification #clustering #fuzzy

Weighted One-Class Classifier Ensemble Based on Fuzzy Feature Space Partitioning (BK, MW, BC), pp. 2838–2843.

ICPR-2014-LiuCVC #classification

Leaf Species Classification Based on a Botanical Shape Sub-classifier Strategy (HL, DC, LV, GC), pp. 1496–1501.

ICPR-2014-LiYLYWH #classification #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-PillaiFR #classification #learning #multi

Learning of Multilabel Classifiers (IP, GF, FR), pp. 3452–3456.

ICPR-2014-RavalTJ #classification #encoding #evaluation #fault #performance #using

Efficient Evaluation of SVM Classifiers Using Error Space Encoding (NR, RVT, CVJ), pp. 4411–4416.

ICPR-2014-Saux #classification #design #interactive

Interactive Design of Object Classifiers in Remote Sensing (BLS), pp. 2572–2577.

ICPR-2014-ZambaniniKK #consistency #evaluation #geometry

Classifying Ancient Coins by Local Feature Matching and Pairwise Geometric Consistency Evaluation (SZ, AK, MK), pp. 3032–3037.

KDD-2014-PrabhuV #classification #learning #multi #named #performance

FastXML: a fast, accurate and stable tree-classifier for extreme multi-label learning (YP, MV), pp. 263–272.

KDIR-2014-MohammadiMBRA #classification #graph #parametricity

A Noise Resilient and Non-parametric Graph-based Classifier (MM, SAM, EB, BR, AA), pp. 170–175.

MLDM-2014-FuMD #classification #multi #network #performance #towards

Towards the Efficient Recovery of General Multi-Dimensional Bayesian Network Classifier (SF, SM, MCD), pp. 16–30.

MLDM-2014-JavedA #classification #dataset #network #social #using

Creation of Bi-lingual Social Network Dataset Using Classifiers (IJ, HA), pp. 523–533.

MLDM-2014-LarinSKKHC #classification #parametricity #representation #using

Parametric Representation of Objects in Color Space Using One-Class Classifiers (AL, OS, AK, SYK, SCH, BHC), pp. 300–314.

RE-2014-MasseyRAS #ambiguity #identification #requirements

Identifying and classifying ambiguity for regulatory requirements (AKM, RLR, AIA, PPS), pp. 83–92.

SAC-2014-BarddalGE #classification #concept #named #network #social

SFNClassifier: a scale-free social network method to handle concept drift (JPB, HMG, FE), pp. 786–791.

SAC-2014-GomesE #adaptation #classification #data type #named #social

SAE2: advances on the social adaptive ensemble classifier for data streams (HMG, FE), pp. 798–804.

SAC-2014-ZimmermannNS #adaptation #classification

Adaptive semi supervised opinion classifier with forgetting mechanism (MZ, EN, MS), pp. 805–812.

TAP-2014-JannesariKSW #classification #generative #parallel #testing

Generating Classified Parallel Unit Tests (AJ, NK, JS, FW), pp. 117–133.

DocEng-2013-AlvaroZ #layout

A shape-based layout descriptor for classifying spatial relationships in handwritten math (FA, RZ), pp. 123–126.

ICDAR-2013-BaechlerLI #classification #using

Text Line Extraction Using DMLP Classifiers for Historical Manuscripts (MB, ML, RI), pp. 1029–1033.

ICDAR-2013-HigaH #classification #image #recognition

Local Subspace Classifier with Transformation Invariance for Appearance-Based Character Recognition in Natural Images (KH, SH), pp. 533–537.

ICDAR-2013-HuC #classification #pseudo #using #verification

Offline Signature Verification Using Real Adaboost Classifier Combination of Pseudo-dynamic Features (JH, YC), pp. 1345–1349.

ICDAR-2013-KhayyatLS #classification #verification #word

Verification of Hierarchical Classifier Results for Handwritten Arabic Word Spotting (MK, LL, CYS), pp. 572–576.

ICDAR-2013-KimLT #classification #heuristic #identification #using

Identification of Investigator Name Zones Using SVM Classifiers and Heuristic Rules (JK, DXL, GRT), pp. 140–144.

ICDAR-2013-WeiBSI #analysis #classification #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 #classification #sorting

Sorting-Based Dynamic Classifier Ensemble Selection (YY, XCY, ZBW, XY, CY, HWH), pp. 673–677.

CSMR-2013-JamshidiGAP #architecture #evolution #framework #research

A Framework for Classifying and Comparing Architecture-centric Software Evolution Research (PJ, MG, AA, CP), pp. 305–314.

CSCW-2013-MinWHZ #mining #smarttech #social

Mining smartphone data to classify life-facets of social relationships (JKM, JW, JIH, JZ), pp. 285–294.

DUXU-NTE-2013-KulkarniW #energy #using

Classifying Energy-Related Events Using Electromagnetic Field Signatures (ASK, KCW), pp. 105–111.

HCI-III-2013-XuGC #classification #kernel #representation

Kernel Based Weighted Group Sparse Representation Classifier (BX, PG, CLPC), pp. 236–245.

ICEIS-v2-2013-KandjaniMAS #concept #framework #information management

A Conceptual Framework to Classify Strategic Information Systems Planning Methodologies (HK, AM, AEA, RS), pp. 190–196.

CIKM-2013-SeverynNM #classification #ranking

Building structures from classifiers for passage reranking (AS, MN, AM), pp. 969–978.

ICML-c1-2013-XuKWC #classification

Cost-Sensitive Tree of Classifiers (ZEX, MJK, KQW, MC), pp. 133–141.

ICML-c3-2013-DurrantK #bound #classification #fault

Sharp Generalization Error Bounds for Randomly-projected Classifiers (RJD, AK), pp. 693–701.

ICML-c3-2013-GermainHLM #adaptation #approach #classification #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 #classification #online #parallel #performance

Algebraic classifiers: a generic approach to fast cross-validation, online training, and parallel training (MI), pp. 648–656.

KDIR-KMIS-2013-CunhaFM #clustering #documentation #integration

Clustering and Classifying Text Documents — A Revisit to Tagging Integration Methods (EC, ÁF, ÓM), pp. 160–168.

MLDM-2013-BijaksanaLA #classification

A Pattern Based Two-Stage Text Classifier (MAB, YL, AA), pp. 169–182.

MLDM-2013-WilliamsHFR #classification #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-KarimM #classification #performance

Revisiting the Performance of Weighted k-Nearest Centroid Neighbor Classifiers (MRK, MM), pp. 332–337.

SIGIR-2013-WebberBLO #classification #effectiveness #evaluation #testing

Sequential testing in classifier evaluation yields biased estimates of effectiveness (WW, MB, DDL, DWO), pp. 933–936.

SIGIR-2013-WebberP #classification

Assessor disagreement and text classifier accuracy (WW, JP), pp. 929–932.

RE-2013-MaxwellAE #empirical

An empirical investigation of software engineers’ ability to classify legal cross-references (JCM, AIA, JBE), pp. 24–31.

SAC-2013-BlondelSU #classification #constraints #learning #using

Learning non-linear classifiers with a sparsity constraint using L1 regularization (MB, KS, KU), pp. 167–169.

SLE-2013-LammelMV #tool support #wiki

Method and Tool Support for Classifying Software Languages with Wikipedia (RL, DM, AV), pp. 249–259.

VMCAI-2013-SlabyST #classification #database #named

ClabureDB: Classified Bug-Reports Database (JS, JS, MT), pp. 268–274.

DRR-2012-KimLT #classification #identification

Combining SVM classifiers to identify investigator name zones in biomedical articles (JK, DXL, GRT).

CIKM-2012-EldardiryN #analysis #classification #graph #how #predict

An analysis of how ensembles of collective classifiers improve predictions in graphs (HE, JN), pp. 225–234.

CIKM-2012-PatwardhanBAMC

Labeling by landscaping: classifying tokens in context by pruning and decorating trees (SP, BB, AA, AM, JCC), pp. 1133–1142.

ICML-2012-JoulinB #classification

A convex relaxation for weakly supervised classifiers (AJ, FRB), p. 171.

ICPR-2012-BallanBBSSZ #category theory #generative #image #modelling #social

Combining generative and discriminative models for classifying social images from 101 object categories (LB, MB, ADB, AMS, GS, BFZ), pp. 1731–1734.

ICPR-2012-Berrar #classification #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-BougesCBL #classification #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-ConnollyGS #classification #correlation #on the

On the correlation between genotype and classifier diversity (JFC, EG, RS), pp. 1068–1071.

ICPR-2012-CoronaTG #classification #multi #named #web #web service

SuStorID: A multiple classifier system for the protection of web services (IC, RT, GG), pp. 2375–2378.

ICPR-2012-DongYDWYGSM #classification #linear

A Linear Max K-min classifier (MD, LY, WD, QW, CY, JG, LS, LM), pp. 2967–2971.

ICPR-2012-GlodekSPS #classification #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-KrawczykS #analysis #classification #effectiveness #multi

Effective multiple classifier systems for breast thermogram analysis (BK, GS), pp. 3345–3348.

ICPR-2012-KrijtheHL #classification #using

Improving cross-validation based classifier selection using meta-learning (JHK, TKH, ML), pp. 2873–2876.

ICPR-2012-MaoYLZ #classification #invariant #verification

Age-invariant face verification based on Local Classifier Ensemble (XJM, YBY, NL, YZ), pp. 2408–2411.

ICPR-2012-PillaiFR #classification #multi #optimisation

F-measure optimisation in multi-label classifiers (IP, GF, FR), pp. 2424–2427.

ICPR-2012-SharmaHN #classification #detection #incremental #learning #performance

Efficient incremental learning of boosted classifiers for object detection (PS, CH, RN), pp. 3248–3251.

ICPR-2012-SjobergKIL #classification #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-TuS #adaptation #classification #learning

Dynamical ensemble learning with model-friendly classifiers for domain adaptation (WT, SS), pp. 1181–1184.

ICPR-2012-TyagiKFSR #classification #identification

Fusing biographical and biometric classifiers for improved person identification (VT, HPK, TAF, LVS, NKR), pp. 2351–2354.

ICPR-2012-VieiraLSC #distance #invariant #matrix

Distance matrices as invariant features for classifying MoCap data (AWV, TL, WRS, MFMC), pp. 2934–2937.

ICPR-2012-XueCH #classification #constraints #kernel

Discriminative indefinite kernel classifier from pairwise constraints and unlabeled data (HX, SC, JH), pp. 497–500.

ICPR-2012-YeKC #classification #multi

Combining general multi-class and specific two-class classifiers for improved customized ECG heartbeat classification (CY, BVKVK, MTC), pp. 2428–2431.

MLDM-2012-Garcia-ConstantinoCNRS #approach #automation #classification #summary

A Semi-Automated Approach to Building Text Summarisation Classifiers (MGC, FC, PJN, AR, CS), pp. 495–509.

MLDM-2012-Moreira-MatiasMGB #categorisation #classification #matrix #using

Text Categorization Using an Ensemble Classifier Based on a Mean Co-association Matrix (LMM, JMM, JG, PB), pp. 525–539.

SIGIR-2012-HuO #classification #dataset #using

Genre classification for million song dataset using confidence-based classifiers combination (YH, MO), pp. 1083–1084.

SIGIR-2012-NunzioS #classification #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.

TOOLS-EUROPE-2012-Sureka #component #debugging #learning

Learning to Classify Bug Reports into Components (AS), pp. 288–303.

PADL-2012-Coleman #classification #distributed #policy #specification

Distributed Policy Specification and Interpretation with Classified Advertisements (NC), pp. 198–211.

RE-2012-KnaussDPC #detection #requirements

Detecting and classifying patterns of requirements clarifications (EK, DD, GPC, JCH), pp. 251–260.

CAV-2012-SharmaNA #classification

Interpolants as Classifiers (RS, AVN, AA), pp. 71–87.

ICDAR-2011-ImpedovoP #classification #multi

Updating Knowledge in Feedback-Based Multi-classifier Systems (DI, GP), pp. 227–231.

ICDAR-2011-LinGC #component #documentation

Classifying Textual Components of Bilingual Documents with Decision-Tree Support Vector Machines (XRL, CYG, FC), pp. 498–502.

ICDAR-2011-ZhuN11a #classification #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.

ICSM-2011-DhaliwalKZ #case study #debugging

Classifying field crash reports for fixing bugs: A case study of Mozilla Firefox (TD, FK, YZ), pp. 333–342.

ICSM-2011-SahaRS #automation #framework

An automatic framework for extracting and classifying near-miss clone genealogies (RKS, CKR, KAS), pp. 293–302.

LATA-2011-Gelderie #automaton #regular expression

Classifying Regular Languages via Cascade Products of Automata (MG), pp. 286–297.

DHM-2011-TangoMAP #automation #behaviour #classification

Automation Effects on Driver’s Behaviour When Integrating a PADAS and a Distraction Classifier (FT, LM, RA, OP), pp. 503–512.

ICEIS-v1-2011-PotoleaL #classification #performance

A Comprehensive Study of the Effect of Class Imbalance on the Performance of Classifiers (RP, CL), pp. 14–21.

CIKM-2011-SinghV #named

CQC: classifying questions in CQA websites (AS, KV), pp. 2033–2036.

CIKM-2011-VinzamuriK #classification #convergence #design #using

Designing an ensemble classifier over subspace classifiers using iterative convergence routine (BV, KK), pp. 693–698.

CIKM-2011-ZubiagaSFM #topic #twitter

Classifying trending topics: a typology of conversation triggers on Twitter (AZ, DS, VF, RM), pp. 2461–2464.

ECIR-2011-LipkaS #information management #representation

Classifying with Co-stems — A New Representation for Information Filtering (NL, BS), pp. 307–313.

ICML-2011-Hernandez-OralloFR #classification #cost analysis #performance #visualisation

Brier Curves: a New Cost-Based Visualisation of Classifier Performance (JHO, PAF, CFR), pp. 585–592.

KDD-2011-WilkinsonAN #classification #named #random

CHIRP: a new classifier based on composite hypercubes on iterated random projections (LW, AA, DTN), pp. 6–14.

KDIR-2011-ClariziaCSGN11a #classification #novel #set

A Novel Supervised Text Classifier from a Small Training Set (FC, FC, MDS, LG, PN), pp. 545–553.

KDIR-2011-NguyenLT #classification #image #multi

Cascade of Multi-level Multi-instance Classifiers for Image Annotation (CTN, HVL, TT), pp. 14–23.

MLDM-2011-CataltepeSBE #classification #using

Collective Classification Using Heterogeneous Classifiers (ZÇ, AS, KB, AE), pp. 155–169.

MLDM-2011-Garcia-ConstantinoCNRST #classification #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 #classification #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-LiTM #classification #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-YokotaY #classification #estimation

Quadratically Constrained Maximum a Posteriori Estimation for Binary Classifier (TY, YY), pp. 1–15.

SIGIR-2011-JinY #classification #feature model #image #multi

Integrating hierarchical feature selection and classifier training for multi-label image annotation (CJ, CY), pp. 515–524.

SAC-2011-AntonieB #array

Classifying microarray data with association rules (LA, KB), pp. 94–99.

SAC-2011-LiuSGF #classification #performance

Improving matching performance of DPI traffic classifier (TL, YS, LG, BF), pp. 514–519.

CASE-2010-ParkSR #automation #classification #database

Image-based automated chemical database annotation with ensemble of machine-vision classifiers (JP, KS, GRR), pp. 168–173.

DRR-2010-AwalMV #classification #hybrid #recognition

A hybrid classifier for handwritten mathematical expression recognition (AMA, HM, CVG), pp. 1–10.

DRR-2010-KimLT #classification #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 #classification #documentation #optimisation

Time and space optimization of document content classifiers (DY, HSB, CA), pp. 1–10.

ICPC-2010-Taherkhani #algorithm #classification #sorting

Recognizing Sorting Algorithms with the C4.5 Decision Tree Classifier (AT), pp. 72–75.

SOFTVIS-2010-AdamoliH #analysis #framework #named #performance #visualisation

Trevis: a context tree visualization & analysis framework and its use for classifying performance failure reports (AA, MH), pp. 73–82.

ICEIS-AIDSS-2010-SahaPMB #classification #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-DISI-2010-SchusterJS #using #web

Finding and Classifying Product Relationships using Information from the Public Web (DS, TMJ, AS), pp. 300–309.

CIKM-2010-BennettC #classification #online

Online stratified sampling: evaluating classifiers at web-scale (PNB, VRC), pp. 1581–1584.

CIKM-2010-BerminghamS #microblog #question #sentiment

Classifying sentiment in microblogs: is brevity an advantage? (AB, AFS), pp. 1833–1836.

CIKM-2010-Nitta #classification #documentation #scalability #taxonomy #web

Improving taxonomies for large-scale hierarchical classifiers of web documents (KN), pp. 1649–1652.

CIKM-2010-SonPS #classification #estimation #learning #naive bayes

Learning naïve bayes transfer classifier throughclass-wise test distribution estimation (JWS, SBP, HJS), pp. 1729–1732.

ICML-2010-DembczynskiCH #classification #multi #probability

Bayes Optimal Multilabel Classification via Probabilistic Classifier Chains (KD, WC, EH), pp. 279–286.

ICML-2010-GoldbergE #classification

Boosting Classifiers with Tightened L0-Relaxation Penalties (NG, JE), pp. 383–390.

ICML-2010-LayB #classification #predict #using

Supervised Aggregation of Classifiers using Artificial Prediction Markets (NL, AB), pp. 591–598.

ICML-2010-Ruping #classification #estimation

SVM Classifier Estimation from Group Probabilities (SR), pp. 911–918.

ICPR-2010-AlmaksourAQC #classification #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 #classification #image #segmentation

Human-Area Segmentation by Selecting Similar Silhouette Images Based on Weak-Classifier Response (HA, HF), pp. 3444–3447.

ICPR-2010-BayramDSM #approach #classification

An Ensemble of Classifiers Approach to Steganalysis (SB, AED, HTS, NDM), pp. 4376–4379.

ICPR-2010-CevikalpY #classification #scalability

Large Margin Classifier Based on Affine Hulls (HC, HSY), pp. 21–24.

ICPR-2010-ConduracheMM #classification #segmentation

An LDA-based Relative Hysteresis Classifier with Application to Segmentation of Retinal Vessels (AC, FM, AM), pp. 4202–4205.

ICPR-2010-CordellaSFMF #classification #performance

Combining Single Class Features for Improving Performance of a Two Stage Classifier (LPC, CDS, FF, CM, ASdF), pp. 4352–4355.

ICPR-2010-ErdoganS #classification #framework #learning #linear

A Unifying Framework for Learning the Linear Combiners for Classifier Ensembles (HE, MUS), pp. 2985–2988.

ICPR-2010-FuLTZ #classification #learning #music #naive bayes #retrieval

Learning Naive Bayes Classifiers for Music Classification and Retrieval (ZF, GL, KMT, DZ), pp. 4589–4592.

ICPR-2010-ImpedovoP #classification #evaluation #generative #multi #set

Generating Sets of Classifiers for the Evaluation of Multi-expert Systems (DI, GP), pp. 2166–2169.

ICPR-2010-JiaM #design #using

Classifying Textile Designs Using Bags of Shapes (WJ, SJM), pp. 294–297.

ICPR-2010-KhreichGMS #classification

Boolean Combination of Classifiers in the ROC Space (WK, EG, AM, RS), pp. 4299–4303.

ICPR-2010-KrajewskiBK #case study #classification #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-LawalAM #abduction #classification #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-LiD #classification #multi #verification

Multi-classifier Q-stack Aging Model for Adult Face Verification (WL, AD), pp. 1310–1313.

ICPR-2010-Liu10a #classification #prototype #retrieval

One-Vs-All Training of Prototype Classifier for Pattern Classification and Retrieval (CLL), pp. 3328–3331.

ICPR-2010-MangalampalliCS #classification #fuzzy #image #named #performance

I-FAC: Efficient Fuzzy Associative Classifier for Object Classes in Images (AM, VC, SS), pp. 4388–4391.

ICPR-2010-ManjunathMS #classification #database #relational

A Practical Heterogeneous Classifier for Relational Databases (GM, MNM, DS), pp. 3316–3319.

ICPR-2010-PaclikLLD #analysis #classification #optimisation

ROC Analysis and Cost-Sensitive Optimization for Hierarchical Classifiers (PP, CL, TL, RPWD), pp. 2977–2980.

ICPR-2010-PengSGS #classification #documentation #using

Text Separation from Mixed Documents Using a Tree-Structured Classifier (XP, SS, VG, RS), pp. 241–244.

ICPR-2010-PlumptonKLJ #classification #linear #online #using

On-Line fMRI Data Classification Using Linear and Ensemble Classifiers (COP, LIK, DEJL, SJJ), pp. 4312–4315.

ICPR-2010-Porro-MunozDOTL #difference #representation

Classifying Three-way Seismic Volcanic Data by Dissimilarity Representation (DPM, RPWD, MOA, ITB, JMLB), pp. 814–817.

ICPR-2010-Sato #classification #design #kernel #learning

A New Learning Formulation for Kernel Classifier Design (AS), pp. 2897–2900.

ICPR-2010-SchelsS #approach #classification #image #multi #sequence

A Multiple Classifier System Approach for Facial Expressions in Image Sequences Utilizing GMM Supervectors (MS, FS), pp. 4251–4254.

ICPR-2010-SeyedhosseiniPT #classification #image #network #parsing

Image Parsing with a Three-State Series Neural Network Classifier (MS, ARCP, TT), pp. 4508–4511.

ICPR-2010-SilvaLSBKT #classification #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-SternigRB #classification #learning #multi

Inverse Multiple Instance Learning for Classifier Grids (SS, PMR, HB), pp. 770–773.

ICPR-2010-SzczotFLP #adaptation #classification

Package Boosting for Readaption of Cascaded Classifiers (MS, JF, OL, GP), pp. 552–555.

ICPR-2010-WangH10a #case study #classification #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-WoloszynskiK #classification #random

A Measure of Competence Based on Randomized Reference Classifier for Dynamic Ensemble Selection (TW, MK), pp. 4194–4197.

ICPR-2010-YangC #classification #representation

Sparse Representation Classifier Steered Discriminative Projection (JY, DC), pp. 694–697.

ICPR-2010-ZhangSW #classification #online

A SVM-HMM Based Online Classifier for Handwritten Chemical Symbols (YZ, GS, KW), pp. 1888–1891.

ICPR-2010-ZhangZYK #classification #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 #classification #enterprise #kernel

Gaussian ERP Kernel Classifier for Pulse Waveforms Classification (DZ, WZ, DZ, YL, NL), pp. 2736–2739.

KDD-2010-BozorgiSSV #heuristic #learning #predict

Beyond heuristics: learning to classify vulnerabilities and predict exploits (MB, LKS, SS, GMV), pp. 105–114.

KDD-2010-GaoW #mining #nondeterminism

Direct mining of discriminative patterns for classifying uncertain data (CG, JW), pp. 861–870.

KDD-2010-Lee #classification #learning

Learning to combine discriminative classifiers: confidence based (CHL), pp. 743–752.

KDD-2010-PrengerLVCH #bound #classification #fault

Class-specific error bounds for ensemble classifiers (RJP, TDL, KRV, BYC, WGH), pp. 843–852.

KDD-2010-RaykarKY #classification #design #performance #trade-off

Designing efficient cascaded classifiers: tradeoff between accuracy and cost (VCR, BK, SY), pp. 853–860.

SEKE-2010-MauczkaBG #case study #classification #metric #process

Analyzing the Relationship of Process Metrics And Classified Changes — A Pilot Study (AM, MB, TG), pp. 269–272.

SIGIR-2010-CuiZC #classification #video #web

Content-enriched classifier for web video classification (BC, CZ, GC), pp. 619–626.

SAC-2010-CascaranoCR #classification

Improving cost and accuracy of DPI traffic classifiers (NC, LC, FR), pp. 641–646.

SAC-2010-FernandesLR #classification #random

The impact of random samples in ensemble classifiers (PF, LL, DDAR), pp. 1002–1009.

SAC-2010-HanFD #classification #correlation #recognition

A discriminated correlation classifier for face recognition (ZH, CF, XD), pp. 1485–1490.

SAC-2010-HeraviZ #case study #classification #metric

A study on interestingness measures for associative classifiers (MJH, ORZ), pp. 1039–1046.

SAC-2010-LinsBT #automation #detection #documentation #image

Automatically detecting and classifying noises in document images (RDL, SB, MT), pp. 33–39.

SAC-2010-QinXL #classification #nondeterminism

A Bayesian classifier for uncertain data (BQ, YX, FL), pp. 1010–1014.

FSE-2010-YilmazP #hardware

Combining hardware and software instrumentation to classify program executions (CY, AAP), pp. 67–76.

LDTA-2009-SingerBLPY10 #java

Fundamental Nano-Patterns to Characterize and Classify Java Methods (JS, GB, ML, AP, PY), pp. 191–204.

DRR-2009-Likforman-SulemS #classification #network #recognition

Combination of dynamic Bayesian network classifiers for the recognition of degraded characters (LLS, MS), pp. 1–10.

DRR-2009-ZhangZLT #learning

A semi-supervised learning method to classify grant-support zone in web-based medical articles (XZ, JZ, DXL, GRT), pp. 1–10.

ICDAR-2009-BarratT #image #modelling #network #using

Modeling, Classifying and Annotating Weakly Annotated Images Using Bayesian Network (SB, ST), pp. 1201–1205.

ICDAR-2009-EmmanouilidisBP #classification #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-LuqmanBR #classification #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 #classification #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 #classification #image

Extraction of Characters on Signboards in Natural Scene Images by Stump Classifiers (MM, TY), pp. 1365–1369.

ICDAR-2009-MoghaddamC #automation #classification #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 #classification #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 #classification #comparative #recognition #using

Comparative Study of Devnagari Handwritten Character Recognition Using Different Feature and Classifiers (UP, TW, FK), pp. 1111–1115.

ICDAR-2009-PirloITS #classification #normalisation

Combination of Measurement-Level Classifiers: Output Normalization by Dynamic Time Warping (GP, DI, CAT, ES), pp. 416–420.

ICDAR-2009-PirloTI #classification #multi

A Feedback-Based Multi-Classifier System (GP, CAT, DI), pp. 713–717.

ICDAR-2009-RoyMSS #adaptation #classification #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-SarkarSL #documentation #image

Classifying Foreground Pixels in Document Images (PS, ES, JL), pp. 641–645.

ICDAR-2009-StefanoFFM #classification #evolution #learning #network

Learning Bayesian Networks by Evolution for Classifier Combination (CDS, FF, ASdF, AM), pp. 966–970.

ICDAR-2009-YinHTSN #classification #multi #recognition

Rejection Strategies with Multiple Classifiers for Handwritten Character Recognition (XCY, HWH, YFT, JS, SN), pp. 1126–1130.

ICDAR-2009-ZhuSMHN #classification #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 #classification #naive bayes #privacy

Publishing Naive Bayesian Classifiers: Privacy without Accuracy Loss (BM, CZ), pp. 1173–1185.

CHI-2009-TalbotLKT #classification #interactive #machine learning #multi #named #visualisation

EnsembleMatrix: interactive visualization to support machine learning with multiple classifiers (JT, BL, AK, DST), pp. 1283–1292.

HCI-NIMT-2009-JohnsonK #classification

Ensemble SWLDA Classifiers for the P300 Speller (GDJ, DJK), pp. 551–557.

ICEIS-J-2009-NguyenH #approach #documentation

Frequent Subgraph-Based Approach for Classifying Vietnamese Text Documents (TANH, KH), pp. 299–308.

ICEIS-J-2009-SchclarR #classification #random

Random Projection Ensemble Classifiers (AS, LR), pp. 309–316.

CIKM-2009-SunLL #case study #category theory #classification #performance #predict #what

What makes categories difficult to classify?: a study on predicting classification performance for categories (AS, EPL, YL), pp. 1891–1894.

ECIR-2009-AshkanCAG #query

Classifying and Characterizing Query Intent (AA, CLAC, EA, QG), pp. 578–586.

ICML-2009-DuanTXC #adaptation #classification #multi

Domain adaptation from multiple sources via auxiliary classifiers (LD, IWT, DX, TSC), pp. 289–296.

ICML-2009-GermainLLM #classification #learning #linear

PAC-Bayesian learning of linear classifiers (PG, AL, FL, MM), pp. 353–360.

ICML-2009-KeglB #classification

Boosting products of base classifiers (BK, RBF), pp. 497–504.

ICML-2009-ZhangSFD #learning

Learning non-redundant codebooks for classifying complex objects (WZ, AS, XF, TGD), pp. 1241–1248.

KDD-2009-FormanSR #classification #linear

Feature shaping for linear SVM classifiers (GF, MS, SR), pp. 299–308.

KDIR-2009-ClementeDCR #behaviour #classification #image

Behavior of Different Image Classifiers within a Broad Domain (BC, MLD, AC, PGR), pp. 278–283.

MLDM-2009-DuangsoithongW #analysis #classification

Relevance and Redundancy Analysis for Ensemble Classifiers (RD, TW), pp. 206–220.

MLDM-2009-GaagRFGEBF #classification #network

Aligning Bayesian Network Classifiers with Medical Contexts (LCvdG, SR, AF, AdG, MJCE, FJB, BCJMF), pp. 787–801.

MLDM-2009-HasanG #adaptation #classification #modelling

Sequential EM for Unsupervised Adaptive Gaussian Mixture Model Based Classifier (BASH, JQG), pp. 96–106.

MLDM-2009-LiuYZZZL #classification #scalability

A Large Margin Classifier with Additional Features (XL, JY, EZ, GZ, YZ, ML), pp. 82–95.

SEKE-2009-DoranG #clustering #web

Classifying Web Robots by K-means Clustering (DD, SSG), pp. 97–102.

SIGIR-2009-Nomoto #library #profiling

Classifying library catalogue by author profiling (TN), pp. 644–645.

MoDELS-2009-CuccuruRGT #classification #parametricity #uml

Constraining Type Parameters of UML 2 Templates with Substitutable Classifiers (AC, AR, SG, FT), pp. 644–649.

MoDELS-2009-CuccuruRGT #classification #parametricity #uml

Constraining Type Parameters of UML 2 Templates with Substitutable Classifiers (AC, AR, SG, FT), pp. 644–649.

GPCE-2009-McGacheyHM #java #pervasive

Classifying Java class transformations for pervasive virtualized access (PM, ALH, JEBM), pp. 75–84.

SAC-2009-BacharM #classification #novel #ranking

A novel distance-based classifier built on pattern ranking (DB, RM), pp. 1427–1432.

SAC-2009-LiuTS #classification #complexity #learning #using

Assessing complexity of service-oriented computing using learning classifier systems (LL, ST, HS), pp. 2170–2171.

TLCA-2009-TsukadaI #classification #logic

A Logical Foundation for Environment Classifiers (TT, AI), pp. 341–355.

CHI-2008-GrimesTHSR #memory management

Feasibility and pragmatics of classifying working memory load with an electroencephalograph (DBG, DST, SEH, PS, RPNR), pp. 835–844.

CHI-2008-ShenoyT #image

Human-aided computing: utilizing implicit human processing to classify images (PS, DST), pp. 845–854.

SOFTVIS-2008-SensalireOT #maintenance #tool support #visualisation

Classifying desirable features of software visualization tools for corrective maintenance (MS, PO, ACT), pp. 87–90.

CIKM-2008-HoefelE #classification #learning #sequence

Learning a two-stage SVM/CRF sequence classifier (GH, CE), pp. 271–278.

CIKM-2008-ZhangM #composition #kernel

Classifying networked entities with modularity kernels (DZ, RM), pp. 113–122.

ICML-2008-DekelS #learning

Learning to classify with missing and corrupted features (OD, OS), pp. 216–223.

ICML-2008-DundarWLSR #case study #classification #detection

Polyhedral classifier for target detection: a case study: colorectal cancer (MD, MW, SL, MS, VCR), pp. 288–295.

ICML-2008-PalatucciC #classification #on the #scalability

On the chance accuracies of large collections of classifiers (MP, AC), pp. 744–751.

ICPR-2008-Abd-AlmageedASD #classification #hybrid #using

Document-zone classification using partial least squares and hybrid classifiers (WAA, MA, WS, DSD), pp. 1–4.

ICPR-2008-AdankonC #classification

Help-training for semi-supervised discriminative classifiers. Application to SVM (MMA, MC), pp. 1–4.

ICPR-2008-Bauckhage #classification #detection #probability

Probabilistic Diffusion Classifiers for Object Detection (CB), pp. 1–4.

ICPR-2008-ChenTZ #classification #novel

Spam filtering with several novel bayesian classifiers (CC, YT, CZ), pp. 1–4.

ICPR-2008-ChouaibTTCV #algorithm #classification #feature model #search-based

Feature selection combining genetic algorithm and Adaboost classifiers (HC, ORT, ST, FC, NV), pp. 1–4.

ICPR-2008-GaoL #classification #polynomial #recognition

Combining quadratic classifier and pair discriminators by pairwise coupling for handwritten Chinese character recognition (TFG, CLL), pp. 1–4.

ICPR-2008-Hernandez-RodriguezTC #classification #on the #prototype

On the selection of base prototypes for LAESA and TLAESA classifiers (SHR, JFMT, JACO), pp. 1–4.

ICPR-2008-KarnickMP #approach #classification #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-RysavyFEO #classification #random #segmentation

Classifiability criteria for refining of random walks segmentation (SR, AF, RE, KO), pp. 1–4.

ICPR-2008-UchidaA #classification #recognition

Early recognition of sequential patterns by classifier combination (SU, KA), pp. 1–4.

ICPR-2008-WimmerHS #bound #classification

Implicit active shape model employing boundary classifier (AW, JH, GS), pp. 1–4.

ICPR-2008-WuNC #image #probability

A probabilistic model for classifying segmented images (LW, PN, LNC), pp. 1–4.

ICPR-2008-YamaguchiM #categorisation #classification #image #probability #topic

Image categorization by a classifier based on probabilistic topic model (TY, MM), pp. 1–4.

ICPR-2008-ZhongGA #algorithm #classification

Properties of the k-norm pruning algorithm for decision tree classifiers (MZ, MG, GCA), pp. 1–4.

KDD-2008-ElkanN #classification #learning

Learning classifiers from only positive and unlabeled data (CE, KN), pp. 213–220.

SEKE-2008-LucasSM #classification #personalisation #recommendation #towards

Comparing the Use of Traditional and Associative Classifiers towards Personalized Recommendations (JPL, SS, MNMG), pp. 607–612.

SIGIR-2008-QiD #classification #web

Classifiers without borders: incorporating fielded text from neighboring web pages (XQ, BDD), pp. 643–650.

PPDP-2008-DeckerM #consistency #nondeterminism

Classifying integrity checking methods with regard to inconsistency tolerance (HD, DM), pp. 195–204.

REFSQ-2008-MarincicMW #embedded #requirements #verification

Classifying Assumptions Made during Requirements Verification of Embedded Systems (JM, AM, RW), pp. 141–146.

SAC-2008-LucasCD #classification #fuzzy

General type-2 fuzzy classifiers to land cover classification (LAL, TMC, MRD), pp. 1743–1747.

SAC-2008-MengleG #algorithm #ambiguity #classification #feature model #using

Using ambiguity measure feature selection algorithm for support vector machine classifier (SSRM, NG), pp. 916–920.

SAC-2008-SuKZG #classification #collaboration #machine learning #using

Imputation-boosted collaborative filtering using machine learning classifiers (XS, TMK, XZ, RG), pp. 949–950.

CASE-2007-ChenT #classification #gesture #multi #recognition

Multiple-angle Hand Gesture Recognition by Fusing SVM Classifiers (YTC, KTT), pp. 527–530.

ICDAR-2007-Al-HajjML #classification #recognition #word

Combination of HMM-Based Classifiers for the Recognition of Arabic Handwritten Words (RAHM, CM, LLS), pp. 959–963.

ICDAR-2007-ChouGC #classification #multi #recognition #using

Recognition of Fragmented Characters Using Multiple Feature-Subset Classifiers (CHC, CYG, FC), pp. 198–202.

ICDAR-2007-FuDLL #classification #effectiveness #recognition

An Effective and Practical Classifier Fusion Strategy for Improving Handwritten Character Recognition (QF, XD, TL, CL), pp. 1038–1042.

ICDAR-2007-HirayamaNK #classification #difference #using

A Classifier of Similar Characters using Compound Mahalanobis Function based on Difference Subspace (JH, HN, NK), pp. 432–436.

ICDAR-2007-Hotta #classification #pattern matching #pattern recognition #recognition

Transform-Invariance in Local Averaging Classifier for Handwritten Digit Pattern Recognition (SH), pp. 347–351.

ICDAR-2007-KalvaEK #classification #image #web

WEB Image Classification Based on the Fusion of Image and Text Classifiers (PRK, FE, ALK), pp. 561–568.

ICDAR-2007-LongJ #classification

Building Compact MQDF Classifier for Off-line Handwritten Chinese Characters by Subspace Distribution Sharing (TL, LJ), pp. 909–913.

ICDAR-2007-NguyenBML #classification #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 #classification #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-SunHHFN #classification #recognition

Degraded Character Recognition by Complementary Classifiers Combination (JS, KH, YH, KF, SN), pp. 579–583.

PLDI-2007-NarayanasamyWTEC #analysis #automation

Automatically classifying benign and harmful data racesallusing replay analysis (SN, ZW, JT, AE, BC), pp. 22–31.

LATA-2007-Selivanov

Classifying ω-regular partitions (VLS), pp. 529–540.

DHM-2007-WangYHWJJLZ #classification #hybrid

A Hybrid AB-RBF Classifier for Surface Electromyography Classification (RW, YY, XH, FW, DJ, XJ, FL, JZ), pp. 727–735.

HIMI-MTT-2007-CornsML #approach #development #machine learning #optimisation #using

Development of an Approach for Optimizing the Accuracy of Classifying Claims Narratives Using a Machine Learning Tool (TEXTMINER[4]) (HLC, HRM, MRL), pp. 411–416.

HIMI-MTT-2007-JungSL #collaboration #design #visualisation

Folksonomy-Based Collaborative Tagging System for Classifying Visualized Information in Design Practice (HoJ, MsS, KPL), pp. 298–306.

CIKM-2007-JiangZ #adaptation #approach #classification #statistics

A two-stage approach to domain adaptation for statistical classifiers (JJ, CZ), pp. 401–410.

ECIR-2007-AyacheQG #classification #multi #semantics

Classifier Fusion for SVM-Based Multimedia Semantic Indexing (SA, GQ, JG), pp. 494–504.

ECIR-2007-HeD #classification #naive bayes #using

Improving Naive Bayes Text Classifier Using Smoothing Methods (FH, XD), pp. 703–707.

ICML-2007-EspositoR #algorithm #classification #evaluation #named #performance

CarpeDiem: an algorithm for the fast evaluation of SSL classifiers (RE, DPR), pp. 257–264.

ICML-2007-HeraultG #classification #probability

Sparse probabilistic classifiers (RH, YG), pp. 337–344.

ICML-2007-TomiokaA #matrix

Classifying matrices with a spectral regularization (RT, KA), pp. 895–902.

KDD-2007-KolczY #classification

Raising the baseline for high-precision text classifiers (AK, WtY), pp. 400–409.

KDD-2007-SmithE #bias #classification #generative #robust

Making generative classifiers robust to selection bias (ATS, CE), pp. 657–666.

MLDM-2007-EkdahlK #classification #learning #on the

On Concentration of Discrete Distributions with Applications to Supervised Learning of Classifiers (ME, TK), pp. 2–16.

MLDM-2007-ShidaraNK #classification #consistency #named

CCIC: Consistent Common Itemsets Classifier (YS, AN, MK), pp. 490–498.

MLDM-2007-SzepannekBW #classification #on the

On the Combination of Locally Optimal Pairwise Classifiers (GS, BB, CW), pp. 104–116.

SIGIR-2007-StepinskiM #classification

A fact/opinion classifier for news articles (AS, VOM), pp. 807–808.

SAC-2007-Cardoso-CachopoO #categorisation #classification #using

Semi-supervised single-label text categorization using centroid-based classifiers (ACC, ALO), pp. 844–851.

SAC-2007-TanC #classification #using

Using hypothesis margin to boost centroid text classifier (ST, XC), pp. 398–403.

SAC-2007-XiongCL #classification #database #mining #multi #using

Mining multiple private databases using a kNN classifier (LX, SC, LL), pp. 435–440.

DRR-2006-AndraZ #classification #consistency #nearest neighbour

Style consistent nearest neighbor classifier (SA, XZ).

DRR-2006-AsSadhanBSN #classification #comparative #evaluation #recognition #robust

Comparative evaluation of different classifiers for robust distorted-character recognition (BA, ZAB, AES, MN).

DRR-2006-ChellapillaSS #classification

Optimally combining a cascade of classifiers (KC, MS, PYS).

ICPC-2006-FluriG

Classifying Change Types for Qualifying Change Couplings (BF, HCG), pp. 35–45.

CIKM-2006-XiaoLXM #case study #comparative #web

A comparative study on classifying the functions of web page blocks (XX, QL, XX, WYM), pp. 776–777.

ECIR-2006-KeBO #classification #email #named

PERC: A Personal Email Classifier (SWK, CB, MPO), pp. 460–463.

ECIR-2006-YinP #adaptation #classification #naive bayes #rank

Adapting the Naive Bayes Classifier to Rank Procedural Texts (LY, RP), pp. 179–190.

ICML-2006-DenisMR #classification #learning #naive bayes #performance

Efficient learning of Naive Bayes classifiers under class-conditional classification noise (FD, CNM, LR), pp. 265–272.

ICML-2006-LeeGW #classification #using

Using query-specific variance estimates to combine Bayesian classifiers (CHL, RG, SW), pp. 529–536.

ICML-2006-ReyzinS #classification #complexity #how

How boosting the margin can also boost classifier complexity (LR, RES), pp. 753–760.

ICML-2006-SongE #human-computer #interface #learning

Classifying EEG for brain-computer interfaces: learning optimal filters for dynamical system features (LS, JE), pp. 857–864.

ICML-2006-SuZ #classification #network

Full Bayesian network classifiers (JS, HZ), pp. 897–904.

ICPR-v1-2006-AnC #dataset

Finding Rule Groups to Classify High Dimensional Gene Expression Datasets (JA, YPPC), pp. 1196–1199.

ICPR-v1-2006-ConduracheA #2d #classification #image #linear #segmentation #using

Vessel Segmentation in 2D-Projection Images Using a Supervised Linear Hysteresis Classifier (AC, TA), pp. 343–346.

ICPR-v1-2006-WongC #classification #gesture #recognition #using

Continuous Gesture Recognition using a Sparse Bayesian Classifier (SFW, RC), pp. 1084–1087.

ICPR-v1-2006-ZhangLSC #classification #corpus #performance

An Efficient SVM Classifier for Lopsided Corpora (XZ, BCL, WS, LC), pp. 1144–1147.

ICPR-v2-2006-BertolamiB #classification #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-Ekbal #classification #predict #using

Improvement of Prediction Accuracy Using Discretization and Voting Classifier (AE), pp. 695–698.

ICPR-v2-2006-GaoLL #approach #classification #learning #optimisation

An ensemble classifier learning approach to ROC optimization (SG, CHL, JHL), pp. 679–682.

ICPR-v2-2006-GuptaRPH #classification

Classifiers for Motion (MDG, SR, NP, TSH), pp. 593–596.

ICPR-v2-2006-Hotta #adaptation #classification

Adaptive Weighting of Local Classifiers by Particle Filter (KH), pp. 610–613.

ICPR-v2-2006-HuD #classification #multi #theorem

A “No Panacea Theorem” for Multiple Classifier Combination (RH, RID), pp. 1250–1253.

ICPR-v2-2006-Liu #classification #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-QinWHG #automation #classification

Unsupervised Texture Classification: Automatically Discover and Classify Texture Patterns (LQ, WW, QH, WG), pp. 433–436.

ICPR-v2-2006-Sarkar #classification #image #visual notation

Image classification: Classifying distributions of visual features (PS), pp. 472–475.

ICPR-v2-2006-SuSCG #classification #recognition

Patch-Based Gabor Fisher Classifier for Face Recognition (YS, SS, XC, WG), pp. 528–531.

ICPR-v2-2006-ThakoorJWG #classification

Occlusion Resistant Shape Classifier based onWarped Optimal Path Matching (NT, SJ, QW, JG), pp. 60–63.

ICPR-v2-2006-YangL #analysis #automation #component

Automatic Physiognomic Analysis by Classifying Facial Component Feature (HDY, SWL), pp. 1212–1215.

ICPR-v2-2006-YaslanC #classification #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 #classification #kernel

An Approach for Constructing Sparse Kernel Classifier (ZY, YQ, YY, NZ), pp. 560–563.

ICPR-v2-2006-ZhangC #classification #locality

Comparing Different Localization Approaches of the Radon Transform for Road Centerline Extraction from Classified Satellite Imagery (QZ, IC), pp. 138–141.

ICPR-v3-2006-AbdulkaderDZ #classification #comparative

Comparative Classifier Aggregation (AA, JAD, QZ), pp. 156–159.

ICPR-v3-2006-AnLV #classification #performance

Efficient Cross-validation of the Complete Two Stages in KFD Classifier Formulation (SA, WL, SV), pp. 240–244.

ICPR-v3-2006-BeveridgeSR #classification #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-HuS06a #classification #clustering #functional #image #normalisation

Normalization of Functional Magnetic Resonance Images by Classified Cerebrospinal Fluid Cluster (ZH, PS), pp. 938–941.

ICPR-v3-2006-LouJ #adaptation #classification #nearest neighbour #novel

Novel Adaptive Nearest Neighbor Classifiers Based On Hit-Distance (ZL, ZJ), pp. 87–90.

ICPR-v3-2006-Martinez-ArroyoS #classification #learning #naive bayes

Learning an Optimal Naive Bayes Classifier (MMA, LES), pp. 1236–1239.

ICPR-v3-2006-MatosC #classification #network

Combining global and local classifiers with Bayesian network (LNM, JMdC), pp. 1212–1215.

ICPR-v3-2006-WongLY #classification #performance

Improving Text Classifier Performance based on AUC (AKSW, JWTL, DSY), pp. 268–271.

ICPR-v3-2006-WongWC #classification #robust #using

Robust Appearance-based Tracking using a sparse Bayesian classifier (SFW, KYKW, RC), pp. 47–50.

ICPR-v4-2006-Fisher06a #capacity #classification #empirical

An Empirical Model for Saturation and Capacity in Classifier Spaces (RBF), pp. 189–193.

ICPR-v4-2006-JinYSLX #classification #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 #classification #multi #robust #symmetry

Robust Multiclass Ensemble Classifiers via Symmetric Functions (PL, RN), pp. 136–139.

ICPR-v4-2006-Martinez-ArroyoS06a #classification #learning #naive bayes

Learning an Optimal Naive Bayes Classifier (MMA, LES), p. 958.

ICPR-v4-2006-MatosC06a #classification #network

Combining global and local classifiers with Bayesian network (LNM, JMdC), p. 952.

KDD-2006-ArunasalamC #classification #named #top-down

CCCS: a top-down associative classifier for imbalanced class distribution (BA, SC), pp. 517–522.

KDD-2006-BiPOKFSR #classification #detection #symmetry

Computer aided detection via asymmetric cascade of sparse hyperplane classifiers (JB, SP, KO, TK, GF, MS, RBR), pp. 837–844.

KDD-2006-CastanoMTGDCCD #classification #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 #classification #framework #performance #testing

Reverse testing: an efficient framework to select amongst classifiers under sample selection bias (WF, ID), pp. 147–156.

KDD-2006-Forman #classification #fault #roadmap

Quantifying trends accurately despite classifier error and class imbalance (GF), pp. 157–166.

SEKE-2006-SpinolaST #concept #framework #towards #ubiquitous

Towards a Conceptual Framework to Classify Ubiquitous Software Projects (ROS, JLMdS, GHT), pp. 172–175.

SIGIR-2006-Olsson #analysis #classification #set

An analysis of the coupling between training set and neighborhood sizes for the kNN classifier (JSO), pp. 685–686.

SAC-2006-AbidinP #classification #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-ZamolotskikhDC #bias #classification

A methodology for comparing classifiers that allow the control of bias (AZ, SJD, PC), pp. 582–587.

ICSE-2006-AbeMKKH #classification #estimation #using

Estimation of project success using Bayesian classifier (SA, OM, TK, NK, MH), pp. 600–603.

WICSA-2005-PiattiniCA #architecture #quality #research

Classifying Software Architecture Quality Research (MP, CC, HA), pp. 195–196.

DocEng-2005-TannierGM #xml

Classifying XML tags through “reading contexts” (XT, JJG, MM), pp. 143–145.

ICDAR-2005-BhattacharyaC #classification #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 #classification #design #recognition

Cascade Classifier : Design and Application to Digit Recognition (JD, HE), pp. 1065–1069.

ICDAR-2005-KangD #classification #multi

Selection of Classifiers for the Construction of Multiple Classifier Systems (HJK, DSD), pp. 1194–1198.

ICDAR-2005-LiuD #classification #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 #classification #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-OliveiraBS05a #classification #optimisation

Improving Cascading Classifiers with Particle Swarm Optimization (LSO, AdSBJ, RS), pp. 570–574.

ICDAR-2005-PrudentE #classification #multi

A Toplogy Based Multi-Classifier System (YP, AE), pp. 670–674.

ICDAR-2005-RadtkeSW #classification #feature model

Intelligent Feature Extraction for Ensemble of Classifiers (PVWR, RS, TW), pp. 866–870.

ICDAR-2005-WangC #classification #using

A Hierarchical Classifier Using New Support Vector Machine (YCFW, DC), pp. 851–855.

ICML-2005-JingPR #classification #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-KhoussainovHK #classification

Ensembles of biased classifiers (RK, AH, NK), pp. 425–432.

ICML-2005-LavioletteM #bound #classification

PAC-Bayes risk bounds for sample-compressed Gibbs classifiers (FL, MM), pp. 481–488.

ICML-2005-LeiteB #classification #performance #predict

Predicting relative performance of classifiers from samples (RL, PB), pp. 497–503.

ICML-2005-PernkopfB #classification #generative #learning #network #parametricity

Discriminative versus generative parameter and structure learning of Bayesian network classifiers (FP, JAB), pp. 657–664.

ICML-2005-Pietraszek #analysis #classification #optimisation #using

Optimizing abstaining classifiers using ROC analysis (TP), pp. 665–672.

ICML-2005-SonnenburgRS #classification #scalability #sequence

Large scale genomic sequence SVM classifiers (SS, GR, BS), pp. 848–855.

ICML-2005-WuMR #classification #detection #linear #symmetry

Linear Asymmetric Classifier for cascade detectors (JW, MDM, JMR), pp. 988–995.

ICML-2005-WuSB #classification #scalability

Building Sparse Large Margin Classifiers (MW, BS, GHB), pp. 996–1003.

KDD-2005-ChenH #analysis #classification #image #network

A Bayesian network classifier with inverse tree structure for voxelwise magnetic resonance image analysis (RC, EH), pp. 4–12.

KDD-2005-ManeSH #classification #independence #using

Estimating missed actual positives using independent classifiers (SM, JS, SYH), pp. 648–653.

MLDM-2005-Bak #classification #linear #multi

A New Multidimensional Feature Transformation for Linear Classifiers and Its Applications (EB), pp. 275–284.

MLDM-2005-KoK #classification #on the

On ECOC as Binary Ensemble Classifiers (JK, EK), pp. 1–10.

MLDM-2005-LeHS #ambiguity #approach #classification #reasoning #word

An Evidential Reasoning Approach to Weighted Combination of Classifiers for Word Sense Disambiguation (CAL, VNH, AS), pp. 516–525.

MLDM-2005-TakigawaKN #classification #combinator #product line #set #subclass

The Convex Subclass Method: Combinatorial Classifier Based on a Family of Convex Sets (IT, MK, AN), pp. 90–99.

SIGIR-2005-TanCWXGG #classification #using

Using dragpushing to refine centroid text classifiers (ST, XC, BW, HX, MG, YG), pp. 653–654.

SAC-2005-DalkilicS05a #classification #design #implementation #named

Circle: design and implementation of a classifier based on circuit minimization (MMD, AS), pp. 547–548.

SAC-2005-FradkinK #classification #learning

Methods for learning classifier combinations: no clear winner (DF, PBK), pp. 1038–1043.

CBSE-2004-BeckerOR #adaptation #component #fault

Classifying Software Component Interoperability Errors to Support Component Adaption (SB, SO, RHR), pp. 68–83.

DRR-2004-NagyJKLLMS #classification #parametricity

A nonparametric classifier for unsegmented text (GN, AJ, MSK, YL, DPL, SKM, SCS), pp. 102–108.

VLDB-2004-Fan #classification #concept #data type #named

StreamMiner: A Classifier Ensemble-based Engine to Mine Concept-drifting Data Streams (WF), pp. 1257–1260.

ESOP-2004-CalcagnoMT #classification

ML-Like Inference for Classifiers (CC, EM, WT), pp. 79–93.

ICEIS-v2-2004-KotsiantisP #classification #hybrid #using

A Hybrid Decision Support Tool — Using Ensemble of Classifiers (SBK, PEP), pp. 448–456.

ICEIS-v4-2004-MazhelisP #classification #detection

Combining One-Class Classifiers for Mobile-User Substitution Detection (OM, SP), pp. 130–137.

ICML-2004-Bouckaert #classification #learning

Estimating replicability of classifier learning experiments (RRB).

ICML-2004-FerriFH #classification

Delegating classifiers (CF, PAF, JHO).

ICML-2004-GrossmanD #classification #learning #network

Learning Bayesian network classifiers by maximizing conditional likelihood (DG, PMD).

ICML-2004-HuangYKL #classification #learning #scalability

Learning large margin classifiers locally and globally (KH, HY, IK, MRL).

ICML-2004-LebanonL #classification #multi

Hyperplane margin classifiers on the multinomial manifold (GL, JDL).

ICML-2004-Zadrozny #bias #classification #learning

Learning and evaluating classifiers under sample selection bias (BZ).

ICPR-v1-2004-DmitryD #algorithm #classification #effectiveness

Data Dependent Classifier Fusion for Construction of Stable Effective Algorithms (DV, DK), pp. 144–147.

ICPR-v1-2004-DuinPT #classification #problem

The Characterization of Classification Problems by Classifier Disagreements (RPWD, EP, DMJT), pp. 140–143.

ICPR-v1-2004-GarainCG #classification #multi #recognition

A Multiple-Classifier System for Recognition of Printed Mathematical Symbols (UG, BBC, RPG), pp. 380–383.

ICPR-v1-2004-GocciaSD #classification #fuzzy #learning #recognition

Learning Optimal Classifier Through Fuzzy Recognition Rate Maximization (MG, CS, SGD), pp. 204–207.

ICPR-v1-2004-Jager #classification

Informational Classifier Fusion (SJ), pp. 216–219.

ICPR-v1-2004-KangD #approximate #bound #classification #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-LeydierBE #adaptation #classification #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 #classification #design

SVM-Based Classifier Design with Controlled Confidence (ML, IKS), pp. 164–167.

ICPR-v1-2004-LiuM #classification #recognition #string

Handwritten Numeral String Recognition: Character-Level vs. String-Level Classifier Training (CLL, KM), pp. 405–408.

ICPR-v1-2004-MansillaH #classification #on the

On Classifier Domains of Competence (EBiM, TKH), pp. 136–139.

ICPR-v1-2004-YiKZ #classification #learning

Classifier Combination based on Active Learning (XY, ZK, CZ), pp. 184–187.

ICPR-v1-2004-ZouariHLA #classification #performance #simulation

Simulating Classifier Ensembles of Fixed Diversity for Studying Plurality Voting Performance (HZ, LH, YL, AMA), pp. 232–235.

ICPR-v2-2004-BoutellL #image

Incorporating Temporal Context with Content for Classifying Image Collections (MRB, JL), pp. 947–950.

ICPR-v2-2004-HuR #classification #clustering #probability #using

Probability Table Compression Using Distributional Clustering for Scanning N-Tuple Classifiers (JH, ER), pp. 533–536.

ICPR-v2-2004-MozaffarifK #classification #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-WashizawaY #classification #kernel #pattern matching #pattern recognition #recognition

Kernel Sample Space Projection Classifier for Pattern Recognition (YW, YY), pp. 435–438.

ICPR-v2-2004-YamaguchiM #classification #image

Character Extraction from Natural Scene Images by Hierarchical Classifiers (TY, MM), pp. 687–690.

ICPR-v3-2004-KatoW #algorithm #classification #nearest neighbour #performance

Direct Condensing: An Efficient Voronoi Condensing Algorithm for Nearest Neighbor Classifiers (TK, TW), pp. 474–477.

ICPR-v3-2004-KuhlKWK #classification #using

Training of Classifiers Using Virtual Samples Only (AK, LK, CW, UK), pp. 418–421.

ICPR-v3-2004-LiCKG #classification #detection #image

Detecting Abnormal Regions in Colonoscopic Images by Patch-based Classifier Ensemble (PL, KLC, SMK, YG), pp. 774–777.

ICPR-v3-2004-MitaniMH #image

Artificial Images for Classifying Diffuse Lung Opacities in Thin-Section Computed Tomography Images (YM, NM, YH), pp. 530–533.

ICPR-v3-2004-ReiterR #classification #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 #classification #learning

Critical Vector Learning to Construct RBF Classifiers (DS, GSN, JG, DSY), pp. 359–362.

ICPR-v3-2004-Windeatt #classification #design

Diversity/Accuracy and Ensemble Classifier Design (TW), pp. 454–457.

ICPR-v4-2004-GorgevikC #classification #performance #recognition

An Efficient Three-Stage Classifier for Handwritten Digit Recognition (DG, DC), pp. 507–510.

ICPR-v4-2004-LimJ #classification #image

Cascading Classifiers for Consumer Image Indexing (JHL, JSJ), pp. 897–900.

ICPR-v4-2004-LiuWLT #classification #recognition

Nearest Intra-Class Space Classifier for Face Recognition (WL, YW, SZL, TT), pp. 495–498.

ICPR-v4-2004-NandedkarB #architecture #classification #fuzzy #network

A Fuzzy Min-Max Neural Network Classifier with Compensatory Neuron Architecture (AVN, PKB), pp. 553–556.

ICPR-v4-2004-PrasadSK #image #set #using

Feature Subset Selection using ICA for Classifying Emphysema in HRCT Images (MNP, AS, IK), pp. 515–518.

ICPR-v4-2004-ViswanathMB #classification #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-AksoyKTM #classification #image #interactive #mining

Interactive training of advanced classifiers for mining remote sensing image archives (SA, KK, CT, GBM), pp. 773–782.

SEKE-2004-KhoshgoftaarJ #case study #classification #quality

Noise Elimination with Ensemble-Classifier Filtering: A Case-Study in Software Quality Engineerin (TMK, VHJ), pp. 226–231.

SIGIR-2004-FanL #classification #semantics #video

Semantic video classification by integrating unlabeled samples for classifier training (JF, HL), pp. 592–593.

SIGIR-2004-GreevyS #using

Classifying racist texts using a support vector machine (EG, AFS), pp. 468–469.

SIGIR-2004-MladenicBGM #classification #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-Zhang #adaptation #classification #using

Using bayesian priors to combine classifiers for adaptive filtering (YZ0), pp. 345–352.

RE-2004-NurmulianiZW #requirements #sorting #using

Using Card Sorting Technique to Classify Requirements Change (NN, DZ, SPW), pp. 240–248.

SAC-2004-CoutoMS #biology #using #web

Classifying biological articles using web resources (FMC, BM, MJS), pp. 111–115.

DRR-2003-RahmanTA #heuristic #hybrid #web

Exploring a hybrid of support vector machines (SVMs) and a heuristic-based system in classifying web pages (AFRR, YT, HA), pp. 120–127.

ICDAR-2003-GocciaBSD #classification #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-HamamuraMI #classification #multi

A Multiclass Classification Method Based on Multiple Pairwise Classifiers (TH, HM, BI), pp. 809–813.

ICDAR-2003-HaoLS #classification #evaluation

Confidence Evaluation for Combining Diverse Classifiers (HH, CLL, HS), pp. 760–764.

ICDAR-2003-HaoLS03a #algorithm #classification #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 #classification #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 #classification #dependence #higher-order #multi

Combining Multiple Classifiers based on Third-Order Dependency (HJK, DSD), pp. 21–25.

ICDAR-2003-KangD03a #classification #evaluation #multi

Evaluation of the Information-Theoretic Construction of Multiple Classifier Systems (HJK, DSD), pp. 789–793.

ICDAR-2003-MaD #classification #documentation #image #multi

Gabor Filter Based Multi-class Classifier for Scanned Document Images (HM, DSD), pp. 968–972.

ICDAR-2003-PrevostMMOM #classification #modelling #recognition

Combining model-based and discriminative classifiers : application to handwritten character recognition (LP, CMS, AM, LO, MM), p. 31–?.

ICDAR-2003-RagotA #classification #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-StefanoCM #algorithm #classification #reliability #search-based

Exploiting Reliability for Dynamic Selection of Classifiers by Means of Genetic Algorithms (CDS, ADC, AM), pp. 671–675.

ICDAR-2003-VelekN #classification #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-ZouariHLA #classification #parallel

A New Classifier Simulator for Evaluating Parallel Combination Methods (HZ, LH, YL, AMA), pp. 26–30.

ICEIS-v2-2003-YanagidaM #database #self

Classifying Databases By K-Propagated Self-Organizing Map (TY, TM), pp. 499–502.

CIKM-2003-SunL #mining #web

Web unit mining: finding and classifying subgraphs of web pages (AS, EPL), pp. 108–115.

ECIR-2003-Moschitti #case study #classification #parametricity

A Study on Optimal Parameter Tuning for Rocchio Text Classifier (AM), pp. 420–435.

ICML-2003-Jaeger #classification #concept #probability

Probabilistic Classifiers and the Concepts They Recognize (MJ), pp. 266–273.

ICML-2003-KlautauJO #classification #comparison #kernel #modelling

Discriminative Gaussian Mixture Models: A Comparison with Kernel Classifiers (AK, NJ, AO), pp. 353–360.

ICML-2003-LachicheF #classification #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 #classification #learning

Reinforcement Learning as Classification: Leveraging Modern Classifiers (MGL, RP), pp. 424–431.

ICML-2003-PorterEHT #classification #order #scalability #statistics

Weighted Order Statistic Classifiers with Large Rank-Order Margin (RBP, DE, DRH, JT), pp. 600–607.

ICML-2003-RennieSTK #classification #naive bayes

Tackling the Poor Assumptions of Naive Bayes Text Classifiers (JDR, LS, JT, DRK), pp. 616–623.

ICML-2003-YanDMW #approximate #classification #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 #classification #mining

Mining high dimensional data for classifier knowledge (RB, GK, WN), pp. 481–486.

KDD-2003-WangFYH #classification #concept #data type #mining #using

Mining concept-drifting data streams using ensemble classifiers (HW, WF, PSY, JH), pp. 226–235.

KDD-2003-YuYH #clustering #scalability #set #using

Classifying large data sets using SVMs with hierarchical clusters (HY, JY, JH), pp. 306–315.

KDD-2003-ZakiA #classification #effectiveness #named #xml

XRules: an effective structural classifier for XML data (MJZ, CCA), pp. 316–325.

MLDM-2003-EstruchFHR #classification

Simple Mimetic Classifiers (VE, CF, JHO, MJRQ), pp. 156–171.

SIGIR-2003-Bennett #classification #probability #symmetry #using

Using asymmetric distributions to improve text classifier probability estimates (PNB), pp. 111–118.

SIGIR-2003-YangZK #analysis #categorisation #classification #scalability

A scalability analysis of classifiers in text categorization (YY, JZ, BK), pp. 96–103.

POPL-2003-TahaN #classification

Environment classifiers (WT, MFN), pp. 26–37.

SAC-2003-PerrizoDDSDK #incremental #named

PINE — Podium Incremental Neighbor Evaluator for Classifying Spatial Data (WP, QD, AD, KS, QD, MK), pp. 503–508.

ICSE-2003-PodgurskiLFMMSW #automation

Automated Support for Classifying Software Failure Reports (AP, DL, PF, WM, MM, JS, BW), pp. 465–477.

ICSM-2002-LuccaPG #approach #maintenance

An Approach to Classify Software Maintenance Requests (GADL, MDP, SG), pp. 93–102.

ICEIS-2002-SantosNASR #classification #data mining #database #learning #mining #using

Augmented Data Mining over Clinical Databases Using Learning Classifier Systems (MFS, JN, AA, ÁMS, FR), pp. 512–516.

CIKM-2002-ElnaffarMH #automation #database

Automatically classifying database workloads (SE, TPM, RH), pp. 622–624.

ICML-2002-DashC #classification #naive bayes

Exact model averaging with naive Bayesian classifiers (DD, GFC), pp. 91–98.

ICML-2002-DzeroskiZ #classification

Is Combining Classifiers Better than Selecting the Best One (SD, BZ), pp. 123–130.

ICML-2002-Ting #classification #evaluation #using

Issues in Classifier Evaluation using Optimal Cost Curves (KMT), pp. 642–649.

ICML-2002-YangW #classification

Non-Disjoint Discretization for Naive-Bayes Classifiers (YY, GIW), pp. 666–673.

ICPR-v1-2002-ArlandisPC #classification #metric

Rejection Strategies and Confidence Measures for a k- NN Classifier in an OCR Task (JA, JCPC, JCP), pp. 576–579.

ICPR-v1-2002-MitaniYKUMH

Combining the Gabor and Histogram Features for Classifying Diffuse Lung Opacities in Thin-Section Computed Tomography (YM, HY, SK, KU, NM, YH), pp. 53–56.

ICPR-v1-2002-SebeLCGH #classification #naive bayes #recognition #using

Emotion Recognition Using a Cauchy Naive Bayes Classifier (NS, MSL, IC, AG, TSH), p. 17–?.

ICPR-v1-2002-Souafi-BensafiPLE #classification #documentation #network

Bayesian Networks Classifiers Applied to Documents (SSB, MP, FL, HE), p. 483–?.

ICPR-v1-2002-UnsalanB #development #image #statistics #using

Classifying Land Development in High Resolution Satellite Images Using Straight Line Statistics (CÜ, KLB), pp. 127–130.

ICPR-v1-2002-ZhuY #classification #documentation

A New Textual/Non-Textual Classifier for Document Skew Correction (XZ, XY), pp. 480–482.

ICPR-v2-2002-AltyncayD #classification #multi #normalisation #problem #question #why

Why Does Output Normalization Create Problems in Multiple Classifier Systems? (HA, MD), pp. 775–778.

ICPR-v2-2002-BalthasarP #classification #performance

Fast Projection Plane Classifier (DB, LP), pp. 200–203.

ICPR-v2-2002-Duin #classification #question

The Combining Classifier: To Train or Not to Train? (RPWD), pp. 765–770.

ICPR-v2-2002-GargPH #classification #network

Bayesian Networks as Ensemble of Classifiers (AG, VP, TSH), pp. 779–784.

ICPR-v2-2002-GiacintoR #classification #detection #multi #network

Intrusion Detection in Computer Networks by Multiple Classifier Systems (GG, FR), pp. 390–393.

ICPR-v2-2002-LladoP

Classifying Textures when Seen from Different Distances (XL, MP), pp. 909–912.

ICPR-v2-2002-Mustafa #identification #image

Identifying and Classifying Image Transforms (AAYM), pp. 806–809.

ICPR-v2-2002-Paletta #classification #detection #using

Detection of Traffic Signs Using Posterior Classifier Combination (LP), pp. 705–708.

ICPR-v2-2002-RoliFV #analysis #classification #trade-off

Analysis of Error-Reject Trade-off in Linearly Combined Classifiers (FR, GF, GV), pp. 120–125.

ICPR-v2-2002-Schiele #classification #how #question

How Many Classifiers Do I Need? (BS), pp. 176–179.

ICPR-v2-2002-SirlantzisFG #algorithm #classification #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 #classification #multi

An Adaptive Weighted Majority Vote Rule for Combining Multiple Classifiers (CDS, ADC, AM), pp. 192–195.

ICPR-v2-2002-TaxD #classification #multi #using

Using Two-Class Classifiers for Multiclass Classification (DMJT, RPWD), pp. 124–127.

ICPR-v2-2002-Vaswani #classification #linear #matrix

A Linear Classifier for Gaussian Class Conditional Distributions with Unequal Covariance Matrices (NV), pp. 60–63.

ICPR-v2-2002-VeeramachaneniFLN #classification #polynomial

Style-Conscious Quadratic Field Classifier (SV, HF, CLL, GN), pp. 72–75.

ICPR-v3-2002-BaesensECV #classification #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-GorgevikC #classification #recognition

Combining SVM Classifiers for Handwritten Digit Recognition (DG, DC), pp. 102–105.

ICPR-v3-2002-HoqueFG #classification #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 #classification #image #network

A Neural Network Classifier for Occluded Images (TK, TT, YI), pp. 45–48.

ICPR-v3-2002-Kwon #classification #clustering #using

Hangul Tree Classifier for Type Clustering Using Horizontal and Vertical Strokes (YBK), pp. 228–231.

ICPR-v3-2002-LefevreMV #classification #process #segmentation

A Two Level Classifier Process for Audio Segmentation (SL, BM, NV), pp. 891–894.

ICPR-v3-2002-QiP #classification

Context-Sensitive Bayesian Classifiers and Application to Mouse Pressure Pattern Classification (Y(Q, RWP), pp. 448–451.

ICPR-v3-2002-RodriguezSAP #classification #incremental

An Incremental and Hierarchical K-NN Classifier for Handwritten Characters (CR, FBS, ISA, AP), pp. 98–101.

ICPR-v3-2002-SahbiB #classification #detection

Coarse-to-Fine Support Vector Classifiers for Face Detection (HS, NB), pp. 359–362.

ICPR-v3-2002-SilvestreL #bound #classification #optimisation

Optimization of Neural Classifiers Based on Bayesian Decision Boundaries and Idle Neurons Pruning (MRS, LLL), pp. 387–390.

ICPR-v3-2002-WangBR #classification #recognition #word

Combining HMM-Based Two-Pass Classifiers for Off-Line Word Recognition (WW, AB, GR), pp. 151–154.

ICPR-v3-2002-XueG #classification #performance #predict #word

Performance Prediction for Handwritten Word Recognizers and Its Application to Classifier Combination (HX, VG), pp. 241–244.

ICPR-v4-2002-CaputoN #classification #kernel

To Each According to its Need: Kernel Class Specific Classifiers (BC, HN), pp. 94–97.

ICPR-v4-2002-MottlKK #classification #identification #kernel

Support Object Classifiers with Rigid and Elastic Kernel Functions for Face Identification (VM, AK, JK), pp. 205–208.

ICPR-v4-2002-TothCA #classification #fault

A Two-Stage-Classifier for Defect Classification in Optical Media Inspection (DT, AC, TA), pp. 373–376.

KDD-2002-KolczSK #classification #performance #random

Efficient handling of high-dimensional feature spaces by randomized classifier ensembles (AK, XS, JKK), pp. 307–313.

KDD-2002-Olecka #classification #performance

Evaluating classifiers’ performance in a constrained environment (AO), pp. 605–612.

KDD-2002-WuFS #approach #classification #data mining #mining #named

B-EM: a classifier incorporating bootstrap with EM approach for data mining (XW, JF, KRS), pp. 670–675.

KDD-2002-ZadroznyE #classification #multi #probability

Transforming classifier scores into accurate multiclass probability estimates (BZ, CE), pp. 694–699.

SIGIR-2002-BennettDH #classification #modelling #probability #reliability #using

Probabilistic combination of text classifiers using reliability indicators: models and results (PNB, STD, EH), pp. 207–214.

SIGIR-2002-ChaiCN #classification #online

Bayesian online classifiers for text classification and filtering (KMAC, HLC, HTN), pp. 97–104.

SIGIR-2002-KimRL #classification #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 #classification

Study of category score algorithms for k-NN classifier (HK, GG), pp. 393–394.

SAC-2002-NevesBR #classification #game studies #learning

Learning the risk board game with classifier systems (AN, OB, ACR), pp. 585–589.

ICDAR-2001-AkselaLOK #adaptation #classification

Rejection Methods for an Adaptive Committee Classifier (MA, JL, EO, JK), pp. 982–986.

ICDAR-2001-BarakatB #classification #geometry

Training with Positive and Negative Data Samples: Effects on a Classifier for Hand-Drawn Geometric Shapes (HB, DB), pp. 1017–1021.

ICDAR-2001-HoqueF #classification #learning

An Improved Learning Scheme for the Moving Window Classifier (SH, MCF), pp. 607–611.

ICDAR-2001-KangL #classification #multi

Experimental Results on the Construction of Multiple Classifiers Recognizing Handwritten Numerals (HJK, SWL), pp. 1026–1030.

ICDAR-2001-Ratzlaff #classification #online #recognition

A Scanning n-tuple Classifier for Online Recognition of Handwritten Digits (EHR), pp. 18–22.

ICDAR-2001-SirlantzisF #classification #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 #classification #optimisation

Active Digit Classifiers: A Separability Optimization Approach to Emulate Cognition (AT, VG), pp. 401–405.

ICDAR-2001-YeCS #classification #reduction #using

Reduction of the Classification Cost Using Hierarchical Classifiers based on the k-NN Rule (XY, MC, CYS), pp. 716–720.

ICEIS-v2-2001-MorilloFD #analysis #named

RSHP: A Scheme to Classify Information in a Domain Analysis Environment (JLM, JMF, ID), pp. 686–690.

CIKM-2001-Al-KofahiTVTJ #categorisation #classification #multi

Combining Multiple Classifiers for Text Categorization (KAK, AT, AV, TT, PJ), pp. 97–104.

CIKM-2001-GohCC #classification #image

SVM Binary Classifier Ensembles for Image Classification (KG, EYC, KTC), pp. 395–402.

CIKM-2001-SattlerD #classification #database #sql

SQL Database Primitives for Decision Tree Classifiers (KUS, OD), pp. 379–386.

ICML-2001-LangfordSM #bound #classification #predict

An Improved Predictive Accuracy Bound for Averaging Classifiers (JL, MWS, NM), pp. 290–297.

ICML-2001-LatinneSD #classification #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 #classification #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 #classification #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 #classification

Boosting Neighborhood-Based Classifiers (MS, RN, SL), pp. 505–512.

ICML-2001-ShakhnarovichEB #classification #evaluation #statistics

Smoothed Bootstrap and Statistical Data Cloning for Classifier Evaluation (GS, REY, YB), pp. 521–528.

ICML-2001-ZadroznyE #classification #naive bayes #probability

Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers (BZ, CE), pp. 609–616.

KDD-2001-CarageaCH #classification #using

Gaining insights into support vector machine pattern classifiers using projection-based tour methods (DC, DC, VH), pp. 251–256.

KDD-2001-FungM #classification

Proximal support vector machine classifiers (GF, OLM), pp. 77–86.

KDD-2001-IndurkhyaW #classification #problem #rule-based

Solving regression problems with rule-based ensemble classifiers (NI, SMW), pp. 287–292.

MLDM-2001-PhamWS #classification #detection #network

Face Detection by Aggregated Bayesian Network Classifiers (TVP, MW, AWMS), pp. 249–262.

SIGIR-2001-DrewL #classification #using

Construction of a Hierarchical Classifier Schema Using a Combination of Text-Based and Image-Based Approaches (MSD, CL), pp. 438–439.

SIGIR-2001-StokesC #classification #detection #documentation #semantics

Combining Semantic and Syntactic Document Classifiers to Improve First Story Detection (NS, JC), pp. 424–425.

ICML-2000-AllweinSS #approach #classification #multi

Reducing Multiclass to Binary: A Unifying Approach for Margin Classifiers (ELA, RES, YS), pp. 9–16.

ICML-2000-BennettB #classification #geometry

Duality and Geometry in SVM Classifiers (KPB, EJB), pp. 57–64.

ICML-2000-CampbellCS #classification #learning #query #scalability

Query Learning with Large Margin Classifiers (CC, NC, AJS), pp. 111–118.

ICML-2000-Domingos #classification #problem

Bayesian Averaging of Classifiers and the Overfitting Problem (PMD), pp. 223–230.

ICML-2000-HsuHW #classification #naive bayes #why

Why Discretization Works for Naive Bayesian Classifiers (CNH, HJH, TTW), pp. 399–406.

ICML-2000-KaynakA #classification #multi

MultiStage Cascading of Multiple Classifiers: One Man’s Noise is Another Man’s Data (CK, EA), pp. 455–462.

ICML-2000-MargineantuD #classification #evaluation

Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers (DDM, TGD), pp. 583–590.

ICML-2000-MullinS #classification #nearest neighbour

Complete Cross-Validation for Nearest Neighbor Classifiers (MDM, RS), pp. 639–646.

ICML-2000-WilliamsS #classification #kernel

The Effect of the Input Density Distribution on Kernel-based Classifiers (CKIW, MWS), pp. 1159–1166.

ICPR-v1-2000-ClavierTLDL #classification #sorting

Classifiers Combination for Forms Sorting (EC, ÉT, ML, SD, JL), pp. 1932–1935.

ICPR-v2-2000-Abe #classification #fuzzy

Generalization Improvement of a Fuzzy Classifier with Pyramidal Membership Functions (SA), pp. 2211–2214.

ICPR-v2-2000-AchermannB #distance #image

Classifying Range Images of Human Faces with Hausdorff Distance (BA, HB), pp. 2809–2813.

ICPR-v2-2000-AlexandreCK #classification #independence #using

Combining Independent and Unbiased Classifiers Using Weighted Average (LAA, ACC, MSK), pp. 2495–2498.

ICPR-v2-2000-BaggenstossN #classification #probability #using

A Theoretically Optimal Probabilistic Classifier Using Class-Specific Features (PMB, HN), pp. 2763–2768.

ICPR-v2-2000-BeiraghiAAS #classification #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-ChouS #algorithm #classification #learning #multi

A Hierarchical Multiple Classifier Learning Algorithm (YYC, LGS), pp. 2152–2155.

ICPR-v2-2000-Duin #classification

Classifiers in Almost Empty Spaces (RPWD), pp. 2001–2007.

ICPR-v2-2000-GiacintoR #classification #framework

A Theoretical Framework for Dynamic Classifier Selection (GG, FR), pp. 2008–2011.

ICPR-v2-2000-GiacintoRF #classification #clustering #design #effectiveness #multi

Design of Effective Multiple Classifier Systems by Clustering of Classifiers (GG, FR, GF), pp. 2160–2163.

ICPR-v2-2000-HuangCSG #classification #nearest neighbour #prototype

Constructing Optimized Prototypes for Nearest Neighbor Classifiers (YSH, CCC, JWS, WELG), pp. 2017–2020.

ICPR-v2-2000-Kangas #classification #comparison #nearest neighbour #prototype #representation

Comparison between Two Prototype Representation Schemes for a Nearest Neighbor Classifier (JK), pp. 2773–2776.

ICPR-v2-2000-KangL #classification #multi

An Information-Theoretic Strategy for Constructing Multiple Classifier Systems (HJK, SWL), pp. 2483–2486.

ICPR-v2-2000-KimKNS #classification #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 #classification

A Histogram-Based Classifier on Overlapped Bins (MK, HI, MS), pp. 2029–2033.

ICPR-v2-2000-KunchevaWSD #classification #independence #question

Is Independence Good For Combining Classifiers? (LIK, CJW, CAS, RPWD), pp. 2168–2171.

ICPR-v2-2000-LamICTH #approach #multi

A Multi-Window Approach to Classify Histological Features (RWKL, HHSI, KKTC, LHYT, RH), pp. 2259–2262.

ICPR-v2-2000-MalekTA #classification #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-MascarillaF #classification

Another Look at Combining Rejection-Based Pattern Classifiers (LM, CF), pp. 2156–2159.

ICPR-v2-2000-MitaniH #classification #design #nearest neighbour

Classifier Design Based on the Use of Nearest Neighbor Samples (YM, YH), pp. 2769–2772.

ICPR-v2-2000-MiyamotoHM #classification #design #polynomial

Use of Bootstrap Samples in Quadratic Classifier Design (TM, YH, YM), pp. 2789–2792.

ICPR-v2-2000-MollinedaFV #classification #clustering #prototype

A Cluster-Based Merging Strategy for Nearest Prototype Classifiers (RAM, FJF, EV), pp. 2755–2758.

ICPR-v2-2000-MutoNH #classification #evaluation

Evaluation of a Modified Parzen Classifier in High Dimensional Spaces (YM, HN, YH), pp. 2067–2070.

ICPR-v2-2000-NgB #classification #segmentation #using

Supervised Texture Segmentation using DWT and a Modified K-NN Classifier (BWN, AB), pp. 2545–2548.

ICPR-v2-2000-PekalskaD #classification #pattern matching #pattern recognition #recognition

Classifiers for Dissimilarity-Based Pattern Recognition (EP, RPWD), pp. 2012–2016.

ICPR-v2-2000-PerantonisPV #analysis #classification #component #paradigm #using

Supervised Principal Component Analysis Using a Smooth Classifier Paradigm (SJP, SP, VV), pp. 2109–2112.

ICPR-v2-2000-VuoriLOK #adaptation #classification #online #prototype

Controlling On-Line Adaptation of a Prototype-Based Classifier for Handwritten Characters (VV, JL, EO, JK), pp. 2331–2334.

ICPR-v2-2000-WuZZ #classification #network #recognition

A Neural Network Based Classifier for Handwritten Chinese Character Recognition (MW, BZ, LZ), pp. 2561–2564.

ICPR-v2-2000-XiaoWD #adaptation #classification #recognition

Adaptive Combination of Classifiers and its Application to Handwritten Chinese Character Recognition (BX, CHW, RD), pp. 2327–2330.

ICPR-v2-2000-YuJB #classification #recognition #visual notation

Combining Acoustic and Visual Classifiers for the Recognition of Spoken Sentences (KY, XJ, HB), pp. 2491–2494.

ICPR-v2-2000-ZhangDL #classification #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-Nakano #using

Classifying the Motions of Human Body by Using Gabor Wavelets (HN), pp. 3691–3694.

ICPR-v3-2000-SanchisVJ #performance #recognition #speech #verification #word

Efficient Use of the Grammar Scale Factor to Classify Incorrect Words in Speech Recognition Verification (AS, EV, VMJ), pp. 3278–3281.

ICPR-v4-2000-BarataPG #image

Segmenting at Higher Scales to Classify at Lower Scales. A Mathematical Morphology Based Methodology Applied to Forest Cover Remote Sensing Images (TB, PP, IG), pp. 4084–4087.

ICPR-v4-2000-CordellaTV #clustering

Combining Experts with Different Features for Classifying Clustered Microcalcifications in Mammograms (LPC, FT, MV), pp. 4324–4327.

KDD-2000-FungM #classification

Data selection for support vector machine classifiers (GF, OLM), pp. 64–70.

KDD-2000-YiS #classification #documentation

A classifier for semi-structured documents (JY, NS), pp. 340–344.

SIGIR-2000-KimHZ #classification #naive bayes

Text filtering by boosting naive bayes classifiers (YHK, SYH, BTZ), pp. 168–175.

SIGIR-2000-TakasuA #categorisation #classification #comparison

Variance based classifier comparison in text categorization (AT, KA), pp. 316–317.

FSE-2000-NaumovichC #classification

Classifying properties: an alternative to the safety-liveness classification (GN, LAC), pp. 159–168.

ICDAR-1999-AtukoraleS #classification

Combining Classifiers based on Confidence Values (ASA, PNS), pp. 37–40.

ICDAR-1999-KangL #classification #fault

Combining Classifiers based on Minimization of a Bayes Error Rate (HJK, SWL), pp. 398–401.

ICDAR-1999-Kawatani #classification #recognition #using

Handwritten Kanji Recognition using Combined Complementary Classifiers in a Cascade Arrangement (TK), pp. 503–506.

ICDAR-1999-LiuN99a #algorithm #classification #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 #classification #design #distributed #performance #recognition

Designing Efficient Distributed Neural Classifiers: Application to Handwritten Digit Recognition (AR, YL, AE), pp. 265–268.

ICDAR-1999-WuS #classification #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 #classification #proximity #using

Building Hierarchical Classifiers Using Class Proximity (KW, SZ, SCL), pp. 363–374.

WCRE-1999-GannodC #design #framework #reverse engineering

A Framework for Classifying and Comparing Software Reverse Engineering and Design Recovery Techniques (GCG, BHCC), pp. 77–88.

ICML-1999-LangleyS #analysis #classification #naive bayes

Tractable Average-Case Analysis of Naive Bayesian Classifiers (PL, SS), pp. 220–228.

KDD-1999-Domingos #classification #named

MetaCost: A General Method for Making Classifiers Cost-Sensitive (PMD), pp. 155–164.

KDD-1999-KellyHA #classification #performance

The Impact of Changing Populations on Classifier Performance (MGK, DJH, NMA), pp. 367–371.

KDD-1999-MeretakisW #classification #naive bayes #using

Extending Naïve Bayes Classifiers Using Long Itemsets (DM, BW), pp. 165–174.

MLDM-1999-GiacintoR #automation #classification #design #learning #multi

Automatic Design of Multiple Classifier Systems by Unsupervised Learning (GG, FR), pp. 131–143.

UML-1999-MillerW #classification #how #question

How Can Anything be Both a Classifier and a Package? (JM, RWB), pp. 584–597.

ECOOP-1999-BertinoGMM #approach

An Approach to Classify Semi-structured Objects (EB, GG, IM, MM), pp. 416–440.

TOOLS-PACIFIC-1999-JorgensenJ #architecture #component #interactive #product line

Classifying Component Interaction in Product-Line Architectures (BNJ, WJ), pp. 66–77.

VLDB-1998-RastogiS #classification #named

PUBLIC: A Decision Tree Classifier that Integrates Building and Pruning (RR, KS), pp. 404–415.

ICML-1998-Bay #classification #multi #nearest neighbour #set

Combining Nearest Neighbor Classifiers Through Multiple Feature Subsets (SDB), pp. 37–45.

ICML-1998-BollackerG #architecture #classification #reuse #scalability

A Supra-Classifier Architecture for Scalable Knowledge Reuse (KDB, JG), pp. 64–72.

ICML-1998-CristianiniSS #classification #scalability

Bayesian Classifiers Are Large Margin Hyperplanes in a Hilbert Space (NC, JST, PS), pp. 109–117.

ICPR-1998-BischofLP #classification #robust

A robust subspace classifier (HB, AL, FP), pp. 114–116.

ICPR-1998-BreukelenD #classification #network

Neural network initialization by combined classifiers (MvB, RPWD), pp. 215–218.

ICPR-1998-FrelicotL #classification

A pretopology-based supervised pattern classifier (CF, FL), pp. 106–109.

ICPR-1998-HojjatoleslamiK #classification

Strategies for weighted combination of classifiers employing shared and distinct representations (AH, JK), pp. 338–340.

ICPR-1998-HosieVW #behaviour #detection #visual notation

Classifying and detecting group behaviour from visual surveillance data (RH, SV, GAWW), pp. 602–604.

ICPR-1998-Kraaijveld #classification #comparison #parametricity

An experimental comparison of nonparametric classifiers for time-constrained classification tasks (MAK), pp. 428–435.

ICPR-1998-LashkiaA #classification #performance

Test feature classifiers: performance and application (VL, SA), pp. 341–343.

ICPR-1998-NieuwoudtB #classification #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 #classification #nearest neighbour #performance

The labelled cell classifier: a fast approximation to k nearest neighbors (AMP, RRS), pp. 823–827.

ICPR-1998-RodriguezMNZMP #classification

A two-stage classifier for broken and blurred digits in forms (CR, JM, MN, AZ, JIM, JMP), pp. 1101–1105.

KDD-1998-AlsabtiRS #classification #dataset #named #scalability

CLOUDS: A Decision Tree Classifier for Large Datasets (KA, SR, VS), pp. 2–8.

KDD-1998-KohaviS #classification

Targeting Business Users with Decision Table Classifiers (RK, DS), pp. 249–253.

KDD-1998-Stolfo #classification #database #mining

Mining Databases with Different Schemas: Integrating Incompatible Classifiers (ALP, SJS), pp. 314–318.

ECOOP-1998-CrnogoracRR #concurrent #inheritance #object-oriented #programming

Classifying Inheritance Mechanisms in Concurrent Object Oriented Programming (LC, ASR, KR), pp. 571–600.

ICDAR-1997-AlimogluA #classification #multi

Combining Multiple Representations and Classifiers for Pen-based Handwritten Digit Recognitio (FA, EA), pp. 637–640.

ICDAR-1997-AnisimovichRST #classification #recognition #using

Using Combination of Structural, Feature and Raster Classifiers for Recognition of Handprinted Characters (KA, VR, AS, VT), pp. 881–885.

ICDAR-1997-FrankeGKM #classification #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-JunkerH #classification #documentation #learning

Evaluating OCR and Non-OCR Text Representations for Learning Document Classifiers (MJ, RH), pp. 1060–1066.

ICDAR-1997-KangK #classification #framework #multi #probability

Probabilistic Framework for Combining Multiple Classifiers at Abstract Level (HJK, JHK), pp. 870–874.

ICDAR-1997-KawataniS #classification #component #design #difference #using

Complementary Classifier Design Using Difference Principal Components (TK, HS), pp. 875–880.

ICDAR-1997-KimSC #approach #classification #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 #classification #recognition

Static and Dynamic Classifier Fusion for Character Recognition (LP, MM), pp. 499–506.

ICDAR-1997-TeoS #classification #hybrid

A Hybrid Classifier for Recognizing Handwritten Numerals (RYMT, RS), pp. 283–287.

ICML-1997-AskerM #case study #classification #detection #re-engineering

Feature Engineering and Classifier Selection: A Case Study in Venusian Volcano Detection (LA, RM), pp. 3–11.

ICML-1997-KollerS #documentation #using #word

Hierarchically Classifying Documents Using Very Few Words (DK, MS), pp. 170–178.

ICML-1997-VilaltaR #classification #induction #multi

Integrating Feature Construction with Multiple Classifiers in Decision Tree Induction (RV, LAR), pp. 394–402.

KDD-1997-ProvostF #analysis #classification #comparison #performance #visualisation

Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions (FJP, TF), pp. 43–48.

ESEC-FSE-1997-MedvidovicT #architecture #framework

A Framework for Classifying and Comparing Architecture Description Languages (NM, RNT), pp. 60–76.

VLDB-1996-ShaferAM #classification #data mining #mining #named #parallel #scalability

SPRINT: A Scalable Parallel Classifier for Data Mining (JCS, RA, MM), pp. 544–555.

ICML-1996-DomingosP #classification #independence

Beyond Independence: Conditions for the Optimality of the Simple Bayesian Classifier (PMD, MJP), pp. 105–112.

ICML-1996-GreinerGR #classification #learning

Learning Active Classifiers (RG, AJG, DR), pp. 207–215.

ICML-1996-OkamotoY #analysis #classification #nearest neighbour

Theoretical Analysis of the Nearest Neighbor Classifier in Noisy Domains (SO, NY), pp. 355–363.

ICML-1996-SinghP #classification #learning #network #performance

Efficient Learning of Selective Bayesian Network Classifiers (MS, GMP), pp. 453–461.

ICPR-1996-AchermannB #classification #identification

Combination of face classifiers for person identification (BA, HB), pp. 416–420.

ICPR-1996-Bobrowski #classification #learning #set

Piecewise-linear classifiers, formal neurons and separability of the learning sets (LB), pp. 224–228.

ICPR-1996-DiasBD #classification #identification

Results of the use of Bayesian classifiers for identification of breast cancer cell nuclei (ÂVD, FB, MRD), pp. 508–512.

ICPR-1996-HoekstraD #classification #on the

On the nonlinearity of pattern classifiers (AH, RPWD), pp. 271–275.

ICPR-1996-HoK #classification #complexity

Building projectable classifiers of arbitrary complexity (TKH, EMK), pp. 880–885.

ICPR-1996-HwangB #classification #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-KittlerHD #classification

Combining classifiers (JK, MH, RPWD), pp. 897–901.

ICPR-1996-KudoS #classification #using

Selection of classifiers based on the MDL principle using the VC dimension (MK, MS), pp. 886–890.

ICPR-1996-Raudys #classification #design #linear

Linear classifiers in perceptron design (SR), pp. 763–767.

ICPR-1996-RaudysD #classification #empirical #fault

Expected error of minimum empirical error and maximal margin classifiers (SR, VD), pp. 875–879.

ICPR-1996-SkurichinaD #classification

Stabilizing classifiers for very small sample sizes (MS, RPWD), pp. 891–896.

ICPR-1996-StockerRLE #classification #distributed #incremental

Incremental distributed classifier building (ES, AR, YL, AE), pp. 128–132.

ICPR-1996-SzeL #algorithm #bound #branch #classification

Branch and bound algorithm for the Bayes classifier (LS, CHL), pp. 705–709.

ICPR-1996-TumerG #classification #fault

Estimating the Bayes error rate through classifier combining (KT, JG), pp. 695–699.

ICPR-1996-VriesengaS #classification #linear #modelling

Neural modeling of piecewise linear classifiers (MV, JS), pp. 281–285.

ICPR-1996-WouwerSD #analysis #classification #speech

Wavelet-FILVQ classifier for speech analysis (GVdW, PS, DVD), pp. 214–218.

KDD-1996-Kohavi #classification #hybrid #scalability

Scaling Up the Accuracy of Naive-Bayes Classifiers: A Decision-Tree Hybrid (RK), pp. 202–207.

KDD-1996-Sahami #classification #dependence #learning

Learning Limited Dependence Bayesian Classifiers (MS), pp. 335–338.

SIGIR-1996-LarkeyC #categorisation #classification

Combining Classifiers in Text Categorization (LSL, WBC), pp. 289–297.

SIGIR-1996-LewisSCP #algorithm #classification #linear

Training Algorithms for Linear Text Classifiers (DDL, RES, JPC, RP), pp. 298–306.

KBSE-1995-CliftonL #component #design #using

Classifying Software Components Using Design Characteristics (CC, WSL), pp. 139–146.

ICDAR-v1-1995-CaoSA #classification #fuzzy

Fusion of classifiers with fuzzy integrals (JC, MS, MA), pp. 108–111.

ICDAR-v1-1995-HongLHS #classification #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 #classification #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 #classification #formal method #network

A theory of classifier combination: the neural network approach (DSL, SNS), pp. 42–45.

ICDAR-v1-1995-SabourinG #approach #classification #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 #classification #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-TingLHC #classification

A syntactic business form classifier (AT, MKHL, SCH, KYC), pp. 301–304.

ICDAR-v1-1995-UtschickNKSN #classification #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-DrouhardSG #case study #classification #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 #classification #design

Joint feature and classifier design for OCR (DMJ, GN), pp. 1115–1118.

ICDAR-v2-1995-MadhvanathG #classification #recognition #word

Serial classifier combination for handwritten word recognition (SM, VG), pp. 911–914.

ICDAR-v2-1995-MatsunagaK #case study #classification #learning #statistics

An experimental study of learning curves for statistical pattern classifiers (TM, HK), pp. 1103–1106.

ICDAR-v2-1995-WangW #classification #multi #recognition

A multi-layer classifier for recognition of unconstrained handwritten numerals (GEW, JFW), pp. 849–852.

CIKM-1995-TreschL #classification #documentation

An Extensible Classifier for Semi-Structured Documents (MT, AL), pp. 226–233.

ICML-1995-DaganE #classification #probability

Committee-Based Sampling For Training Probabilistic Classifiers (ID, SPE), pp. 150–157.

ICML-1995-SinghP #algorithm #classification #comparison #induction

A Comparison of Induction Algorithms for Selective and non-Selective Bayesian Classifiers (MS, GMP), pp. 497–505.

ICML-1995-SmythGF #classification #estimation #kernel #using

Retrofitting Decision Tree Classifiers Using Kernel Density Estimation (PS, AGG, UMF), pp. 506–514.

KDD-1995-Pazzani #approach #classification

An Iterative Improvement Approach for the Discretization of Numeric Attributes in Bayesian Classifiers (MJP), pp. 228–233.

SEKE-1995-Balmas #comprehension #source code

Classifying Programs: a Key For program Understanding (FB), pp. 342–349.

SIGIR-1995-SchutzeHP #classification #comparison #documentation #problem

A Comparison of Classifiers and Document Representations for the Routing Problem (HS, DAH, JOP), pp. 229–237.

SAC-1995-HalgamugeBG #algorithm #classification #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-Tschichold-Gurman #classification #fuzzy #generative #incremental #learning #using

Generation and improvement of fuzzy classifiers with incremental learning using fuzzy RuleNet (NNTG), pp. 466–470.

EDAC-1994-RobertGMT #classification #design #geometry #realtime

Design of a Real Time Geometric Classifier (MR, PG, JM, ST), p. 656.

SIGIR-1994-LewisG #algorithm #classification

A Sequential Algorithm for Training Text Classifiers (DDL, WAG), pp. 3–12.

SAC-1994-Sen #classification

Representational effects in a simple classifier system (SS), pp. 206–211.

ICDAR-1993-CaesarGM93a #adaptation #classification #scalability #set

Utilization of large disordered sample sets for classifier adaptation in complex domains (TC, JMG, EM), pp. 790–793.

ICDAR-1993-FrankeO #classification #detection #statistics

Writing style detection by statistical combination of classifiers in form reader applications (JF, MFO), pp. 581–584.

ICDAR-1993-HuangS #classification #metric #multi

Combination of multiple classifiers with measurement values (YSH, CYS), pp. 598–601.

ICDAR-1993-NakajimaM #classification #modelling #recognition

A model-based classifier in a scheme of recognition filter (YN, SM), pp. 68–71.

ICDAR-1993-PlessisSHMLDM #classification #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 #classification #recognition

Classifier combination for hand-printed digit recognition (MS, AM, DST, GN), pp. 163–166.

ICDAR-1993-Yan #classification #design #implementation #nearest neighbour #recognition

Design and implementation of optimized nearest neighbor classifiers for handwritten digit recognition (HY), pp. 10–13.

ICDAR-1993-Yan93a #classification #image #nearest neighbour #segmentation #using

Color map image segmentation using optimized nearest neighbor classifiers (HY), pp. 111–114.

ICALP-1993-Wilke #algebra #testing

Algebras for Classifying Regular Tree Languages and an Application to Frontier Testability (TW), pp. 347–358.

SEKE-1993-KomiyaSHKOHOO #analysis #process #specification

An Experimental Analysis for Classifying Specification Processes (SK, MS, SH, JK, AO, HH, SO, KO), pp. 231–234.

VLDB-1992-AgrawalGIIS #classification #database #mining

An Interval Classifier for Database Mining Applications (RA, SPG, TI, BRI, ANS), pp. 560–573.

ML-1992-Venturini #classification #named

AGIL: Solving the Exploration Versus Exploration Dilemma in a single Classifier System Applied to Simulated Robotics (GV), pp. 458–463.

SIGIR-1992-MasandLW #memory management #reasoning #using

Classifying News Stories using Memory Based Reasoning (BMM, GL, DLW), pp. 59–65.

JICSLP-1992-Dix #logic programming #semantics #source code

Classifying Semantics of Disjunctive Logic Programs (JD), pp. 798–812.

ML-1989-HilliardLRP #approach #classification #hybrid #learning #problem #scheduling

Learning Decision Rules for scheduling Problems: A Classifier Hybrid Approach (MRH, GEL, GR, MRP), pp. 188–190.

ECOOP-1989-Briot #design #in the small #named

Actalk: A Testbed for Classifying and Designing Actor Languages in the Smalltalk-80 Environment (JPB), pp. 109–129.

ML-1988-DavisY #classification

Classifier Systems with Hamming Weights (LD, DKY), pp. 162–173.

ML-1988-Quinlan #classification #comparison #empirical #search-based

An Empirical Comparison of Genetic and Decision-Tree Classifiers (JRQ), pp. 135–141.

ML-1988-Robertson #classification

Population Size in classifier Systems (GGR), pp. 142–152.

STOC-1986-BlumerEHW #concept #geometry

Classifying Learnable Geometric Concepts with the Vapnik-Chervonenkis Dimension (Extended Abstract) (AB, AE, DH, MKW), pp. 273–282.

SIGIR-1985-CanasSC #concept #documentation #how #people

A Conceptual Model aod Experiments on How People Classify and Retrieve Documents (AJC, FRS, DWC), pp. 282–287.

ICSE-1984-MiliD #verification

A System for Classifying Program Verification Methods: Assigning Meanings to Program Verification Methods (AM, JD), pp. 499–509.