BibSLEIGH — feature model tag

feature model

feature model

Tag #feature model

754 papers:

SEFM-2019-Dubslaff #composition: Compositional Feature-Oriented Systems (CD), pp. 162–180.
CIKM-2019-ArianAAKSS #network #predict: Feature Enhancement via User Similarities Networks for Improved Click Prediction in Yahoo Gemini Native (MA, EA, MA, YK, OS, RS), pp. 2557–2565.
CIKM-2019-HosseiniH #kernel #learning #multi #prototype #representation: Interpretable Multiple-Kernel Prototype Learning for Discriminative Representation and Feature Selection (BH, BH), pp. 1863–1872.
CIKM-2019-LiCWZW #graph #interactive #modelling #named #network #predict: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction (ZL, ZC, SW, XZ, LW0), pp. 539–548.
CIKM-2019-NiYWLNQC #algorithm #facebook #ranking: Feature Selection for Facebook Feed Ranking System via a Group-Sparsity-Regularized Training Algorithm (XN, YY, PW, YL, SN, QQ, CC), pp. 2085–2088.
CIKM-2019-SongS0DX0T #automation #interactive #learning #named #network #self: AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks (WS, CS, ZX0, ZD, YX, MZ0, JT), pp. 1161–1170.
ICML-2019-BalinAZ #re-engineering: Concrete Autoencoders: Differentiable Feature Selection and Reconstruction (MFB, AA, JYZ), pp. 444–453.
KDD-2019-LiGL0 #adaptation #network: Adaptive Unsupervised Feature Selection on Attributed Networks (JL, RG, CL, HL0), pp. 92–100.
KDD-2019-TranS #predict #scalability: Seasonal-adjustment Based Feature Selection Method for Predicting Epidemic with Large-scale Search Engine Logs (TQT, JS), pp. 2857–2866.
ESEC-FSE-2019-Atlee #interactive: Living with feature interactions (keynote) (JMA), p. 1.
ESEC-FSE-2019-BarashFJRTZ #interactive #ml #requirements #using: Bridging the gap between ML solutions and their business requirements using feature interactions (GB, EF, IJ, OR, RTB, MZ), pp. 1048–1058.
ESEC-FSE-2019-NesicKSB #modelling: Principles of feature modeling (DN, JK, SS, TB), pp. 62–73.
GPCE-2019-FeichtingerHLPG #analysis #constraints #dependence #evolution: Supporting feature model evolution by suggesting constraints from code-level dependency analyses (KF, DH, LL, HP, PG), pp. 129–142.
GPCE-2019-HinterreiterNLS #evolution #modelling #product line: Harmonized temporal feature modeling to uniformly perform, track, analyze, and replay software product line evolution (DH, MN, LL, CS, HP, PG), pp. 115–128.
EDM-2018-PolyzouK #performance #student: Feature extraction for classifying students based on their academic performance (AP, GK).
ICPC-2018-DeLozierDNM #agile #development #process #testing: Leveraging the agile development process for selecting invoking/excluding tests to support feature location (GSD, MJD, CDN, JIM), pp. 370–379.
ICSME-2018-0006LEL #higher-order #interactive #predict: Predicting Higher Order Structural Feature Interactions in Variable Systems (SF0, LL, AE, RELH), pp. 252–263.
MSR-2018-MoslehiAR #using: Feature location using crowd-based screencasts (PM, BA, JR), pp. 192–202.
CIKM-2018-Xu0AWR #consistency #multi: Semi-Supervised Multi-Label Feature Selection by Preserving Feature-Label Space Consistency (YX, JW0, SA, JW, JR), pp. 783–792.
ICML-2018-AghazadehSLDSB #named #scalability #sketching #using: MISSION: Ultra Large-Scale Feature Selection using Count-Sketches (AA, RS, DL, GD, AS, RGB), pp. 80–88.
ICML-2018-Zhao0FYW #estimation #learning: MSplit LBI: Realizing Feature Selection and Dense Estimation Simultaneously in Few-shot and Zero-shot Learning (BZ, XS0, YF, YY0, YW), pp. 5907–5916.
ICPR-2018-0005GHL #image #network #segmentation: Feature Extraction and Grain Segmentation of Sandstone Images Based on Convolutional Neural Networks (FJ0, QG, HH, NL), pp. 2636–2641.
ICPR-2018-Chen18a #analysis #robust: Improved Robust Discriminant Analysis for Feature Extraction (XC), pp. 1444–1449.
ICPR-2018-FasogbonF18a #automation: Automatic Feature Extraction for Wide-angle and Fish-eye Camera Calibration (PF, LF), pp. 2947–2952.
ICPR-2018-JiaZXZH #classification: Superpixel-Based Feature Extraction and Fusion Method for Hyperspectral and LiDAR Classification (SJ, MZ, JX, JZ, QH), pp. 764–769.
ICPR-2018-LiCY #classification #generative #image: Generative Band Feature Enhancement for Hyperspectral Image Classification (JL, FC, DY), pp. 1918–1923.
ICPR-2018-TianZZLW #fine-grained #multi #recognition: Selective Multi-Convolutional Region Feature Extraction based Iterative Discrimination CNN for Fine-Grained Vehicle Model Recognition (YT, WZ, QZ, GL, XW), pp. 3279–3284.
ICPR-2018-WangYGC #classification: Feature Selection Ensemble for Symbolic Data Classification with AHP (MW, XY, CG, YC), pp. 868–873.
ICPR-2018-XuDS #estimation #kernel: Semi-supervised Feature Selection by Mutual Information Based on Kernel Density Estimation (SX, JD, HS), pp. 818–823.
ICPR-2018-XuZL #multi #named #recognition: MSSVT: Multi-scale feature extraction for single face recognition (XX, LZ, FL), pp. 1996–2001.
ICPR-2018-YanXAK #3d #detection #fault: Accumulated Aggregation Shifting Based on Feature Enhancement for Defect Detection on 3D Textured Low-Contrast Surfaces (YY, SX, HA, SK), pp. 2965–2970.
ICPR-2018-ZhengLFLZ #robust: Robust Attentional Pooling via Feature Selection (JZ, TYL, CF0, XL, ZZ), pp. 2038–2043.
ICPR-2018-ZhuDR #classification #flexibility #image: Flexible and Discriminative Non-linear Embedding with Feature Selection for Image Classification (RZ, FD, YR), pp. 3192–3197.
KDD-2018-LianZZCXS #interactive #named #recommendation: xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems (JL, XZ, FZ, ZC, XX0, GS), pp. 1754–1763.
ASE-2018-AbdessalemPNBS #interactive #testing #using: Testing autonomous cars for feature interaction failures using many-objective search (RBA, AP, SN, LCB, TS), pp. 143–154.
ICSE-2018-XueL #integer #multi #optimisation #problem #programming: Multi-objective integer programming approaches for solving optimal feature selection problem: a new perspective on multi-objective optimization problems in SBSE (YX, YFL), pp. 1231–1242.
GPCE-2018-Peldszus0J #analysis #modelling #product line #security: Model-based security analysis of feature-oriented software product lines (SP, DS0, JJ), pp. 93–106.
GPCE-2018-SoaresMNKA #empirical #interactive #specification: Exploring feature interactions without specifications: a controlled experiment (LRS, JM, SN, CK, ESdA), pp. 40–52.
CASE-2018-SolisKOLTZ #development #estimation: Development of a vision-based feature extraction for food intake estimation for a robotic assistive eating device (JS, CK, MO, ALL, YT, CZ), pp. 1105–1109.
ICPC-2017-TangL #identification #variability: Constructing feature model by identifying variability-aware modules (YT, HL), pp. 263–274.
ICSME-2017-FujiokaN #approach #constraints #interactive: Constraints Based Approach to Interactive Feature Location (DF, NN), pp. 499–503.
MSR-2017-GhotraMH #classification #fault #modelling #scalability: A large-scale study of the impact of feature selection techniques on defect classification models (BG, SM, AEH), pp. 146–157.
SCAM-2017-WangPXFZ #interactive #process #recommendation: Contextual Recommendation of Relevant Program Elements in an Interactive Feature Location Process (JW, XP0, ZX, KF, WZ), pp. 61–70.
CIG-2017-GoudelisTKK #3d #classification #effectiveness: 3D cylindrical trace transform based feature extraction for effective human action classification (GG, GT, KK, SDK), pp. 96–103.
CIKM-2017-An0WY #analysis #clustering: Unsupervised Feature Selection with Joint Clustering Analysis (SA, JW0, JW, ZY), pp. 1639–1648.
CIKM-2017-BrayteeLCK #correlation #multi #using: Multi-Label Feature Selection using Correlation Information (AB, WL0, DRC, PJK), pp. 1649–1656.
CIKM-2017-WeiCY: Unsupervised Feature Selection with Heterogeneous Side Information (XW, BC, PSY), pp. 2359–2362.
ECIR-2017-Chehreghani #analysis #problem: Feature-Oriented Analysis of User Profile Completion Problem (MHC), pp. 304–316.
ICML-2017-KaleKLP #adaptation #linear #online #performance: Adaptive Feature Selection: Computationally Efficient Online Sparse Linear Regression under RIP (SK, ZSK, TL, DP), pp. 1780–1788.
KDD-2017-ChengLL #network #social: Unsupervised Feature Selection in Signed Social Networks (KC, JL, HL0), pp. 777–786.
KDD-2017-McNamaraVY #framework #multimodal: Developing a Comprehensive Framework for Multimodal Feature Extraction (QM, AdlV, TY), pp. 1567–1574.
ECMFA-2017-ArcegaFHC #modelling #on the #runtime: On the Influence of Models at Run-Time Traces in Dynamic Feature Location (LA, JF, ØH, CC), pp. 90–105.
ASE-2017-ShiCWLB #analysis #comprehension #fuzzy: Understanding feature requests by leveraging fuzzy method and linguistic analysis (LS, CC, QW0, SL, BWB), pp. 440–450.
ESEC-FSE-2017-KnuppelTMMS #modelling #product line #question #research: Is there a mismatch between real-world feature models and product-line research? (AK, TT, SM, JM, IS), pp. 291–302.
ESEC-FSE-2017-ZibaeenejadZA #interactive: Continuous variable-specific resolutions of feature interactions (MHZ, CZ, JMA), pp. 408–418.
GPCE-2017-LapenaFPC #modelling #natural language: Analyzing the impact of natural language processing over feature location in models (RL, JF, OP, CC), pp. 63–76.
EDM-2016-ShenC #learning #modelling: Aim Low: Correlation-based Feature Selection for Model-based Reinforcement Learning (SS, MC), pp. 507–512.
ICSME-2016-ArmalyKM #automation #case study #estimation #industrial: A Case Study of Automated Feature Location Techniques for Industrial Cost Estimation (AA, JK, CM), pp. 553–562.
ICSME-2016-RahimiC #matrix #named #source code: Artifact: Cassandra Source Code, Feature Descriptions across 27 Versions, with Starting and Ending Version Trace Matrices (MR, JCH), p. 612.
MSR-2016-DintznerDP #commit #named: FEVER: extracting feature-oriented changes from commits (ND, AvD, MP0), pp. 85–96.
SANER-2016-XuXLC #clustering #fault #information management #named #predict: MICHAC: Defect Prediction via Feature Selection Based on Maximal Information Coefficient with Hierarchical Agglomerative Clustering (ZX, JX, JL0, XC), pp. 370–381.
CIKM-2016-ChengLL #interactive #named: FeatureMiner: A Tool for Interactive Feature Selection (KC, JL, HL0), pp. 2445–2448.
CIKM-2016-SousaCRMG #learning #rank: Incorporating Risk-Sensitiveness into Feature Selection for Learning to Rank (DXdS, SDC, TCR, WSM, MAG), pp. 257–266.
CIKM-2016-WangWY #correlation: Supervised Feature Selection by Preserving Class Correlation (JW0, JW, ZY), pp. 1613–1622.
ICML-2016-WiatowskiTSGB #architecture: Discrete Deep Feature Extraction: A Theory and New Architectures (TW, MT, AS, PG, HB), pp. 2149–2158.
ICML-2016-ZhangGR #consistency #on the: On the Consistency of Feature Selection With Lasso for Non-linear Targets (YZ, WG, SR), pp. 183–191.
ICML-2016-ZhangP #markov #modelling: Markov Latent Feature Models (AZ, JWP), pp. 1129–1137.
ICPR-2016-GhoshC: Deep feature extraction in the DCT domain (AG, RC), pp. 3536–3541.
ICPR-2016-KesimanPBO #case study #image #recognition: Study on feature extraction methods for character recognition of Balinese script on palm leaf manuscript images (MWAK, SP, JCB, JMO), pp. 4017–4022.
ICPR-2016-LimK #approach #multi #optimisation: Convex optimization approach for multi-label feature selection based on mutual information (HL, DWK), pp. 1512–1517.
ICPR-2016-NieGJ #framework #integer #programming: An information theoretic feature selection framework based on integer programming (SN, TG, QJ), pp. 3584–3589.
ICPR-2016-SagawaSHOKF #automation #robust #using: Automatic feature extraction using CNN for robust active one-shot scanning (RS, YS, TH, SO, HK, RF), pp. 234–239.
ICPR-2016-SilvaBF #online: Online Weighted One-Class Ensemble for feature selection in background/foreground separation (CS, TB, CF), pp. 2216–2221.
ICPR-2016-ZhengYYY #learning #robust: Robust unsupervised feature selection by nonnegative sparse subspace learning (WZ, HY, JY0, JY), pp. 3615–3620.
ICPR-2016-ZhugeHNY #clustering #graph #using: Unsupervised feature extraction using a learned graph with clustering structure (WZ, CH, FN, DY), pp. 3597–3602.
KDD-2016-LinXBJZ #interactive #learning #multi: Multi-Task Feature Interaction Learning (KL, JX, IMB, SJ, JZ), pp. 1735–1744.
KDD-2016-YangFK0 #algorithm #online #parallel: Online Feature Selection: A Limited-Memory Substitution Algorithm and Its Asynchronous Parallel Variation (HY, RF, YK, JL0), pp. 1945–1954.
MoDELS-2016-FontAHC #algorithm #information retrieval #modelling #search-based: Feature location in models through a genetic algorithm driven by information retrieval techniques (JF, LA, ØH, CC), pp. 272–282.
GPCE-2016-KowalAT #modelling: Explaining anomalies in feature models (MK, SA, TT), pp. 132–143.
FASE-2016-WeckesserLSRS #automation #bound #detection #exclamation #modelling: Mind the Gap! Automated Anomaly Detection for Potentially Unbounded Cardinality-Based Feature Models (MW, ML, TS, BR, AS), pp. 158–175.
ICST-2016-ArcainiGV #automation #consistency #detection #fault #modelling: Automatic Detection and Removal of Conformance Faults in Feature Models (PA, AG, PV), pp. 102–112.
ECSA-2015-TahriDP #architecture #deployment #distributed #modelling #smarttech #using: Using Feature Models for Distributed Deployment in Extended Smart Home Architecture (AT, LD, JP), pp. 285–293.
ICPC-2015-BeckDVWP #user interface: Rethinking user interfaces for feature location (FB, BD, JVM, DW, DP), pp. 151–162.
ICPC-2015-HillSP #evaluation #using: Exploring the use of concern element role information in feature location evaluation (EH, DCS, LLP), pp. 140–150.
ICPC-2015-JordanRHBB #industrial #source code: Manually locating features in industrial source code: the search actions of software nomads (HRJ, JR, SH, GB, JB), pp. 174–177.
ICSME-2015-CorleyDK #learning #using: Exploring the use of deep learning for feature location (CSC, KD, NAK), pp. 556–560.
ICSME-2015-CorleyKK #modelling #topic: Modeling changeset topics for feature location (CSC, KLK, NAK), pp. 71–80.
ICSME-2015-LeLL #fault: Constrained feature selection for localizing faults (TDBL, DL, ML), pp. 501–505.
SANER-2015-LianZ #non-functional #product line #requirements #towards: Optimized feature selection towards functional and non-functional requirements in Software Product Lines (XL, LZ), pp. 191–200.
SCAM-2015-ChochlovEB #data flow #using: Using changeset descriptions as a data source to assist feature location (MC, ME, JB), pp. 51–60.
FM-2015-SafilianMD #formal method #modelling #semantics: The Semantics of Cardinality-Based Feature Models via Formal Languages (AS, TSEM, ZD), pp. 453–469.
CIKM-2015-HuangYK #data type: Unsupervised Feature Selection on Data Streams (HH, SY, SPK), pp. 1031–1040.
CIKM-2015-LiHTL #social #social media #streaming: Unsupervised Streaming Feature Selection in Social Media (JL, XH, JT, HL0), pp. 1041–1050.
ICML-2015-Hernandez-Lobato #multi #probability: A Probabilistic Model for Dirty Multi-task Feature Selection (DHL, JMHL, ZG), pp. 1073–1082.
ICML-2015-XiaoBBFER #question: Is Feature Selection Secure against Training Data Poisoning? (HX, BB, GB, GF, CE, FR), pp. 1689–1698.
KDD-2015-DuS #adaptation #learning: Unsupervised Feature Selection with Adaptive Structure Learning (LD, YDS), pp. 209–218.
MLDM-2015-Perner #automation #image #mining: Automatic Cell Tracking and Kinetic Feature Description of Cell Paths for Image Mining (PP), pp. 441–451.
SEKE-2015-WangKN #re-engineering: Stability of Three Forms of Feature Selection Methods on Software Engineering Data (HW, TMK, AN), pp. 385–390.
MoDELS-2015-LettnerEGP #case study #experience #industrial #lessons learnt #modelling #scalability: Feature modeling of two large-scale industrial software systems: Experiences and lessons learned (DL, KE, PG, HP), pp. 386–395.
SPLC-2015-BecanBGA #modelling #synthesis: Synthesis of attributed feature models from product descriptions (GB, RB, AG, MA), pp. 1–10.
SPLC-2015-Beuche #modelling #variability: Managing variability with feature models (DB), p. 386.
SPLC-2015-ChavarriagaRNCJ #case study #configuration management #experience #modelling #multi #using: Using multiple feature models to specify configuration options for electrical transformers: an experience report (JC, CR, CN, RC, VJ), pp. 216–224.
SPLC-2015-FerrariSGD #diagrams #documentation #natural language #tool support: CMT and FDE: tools to bridge the gap between natural language documents and feature diagrams (AF, GOS, SG, FD), pp. 402–410.
SPLC-2015-LiangGCR #analysis #modelling #satisfiability #scalability: SAT-based analysis of large real-world feature models is easy (JH(L, VG, KC, VR), pp. 91–100.
SPLC-2015-SoutoGdMKB #debugging #detection #modelling #performance #product line: Faster bug detection for software product lines with incomplete feature models (SS, DG, Md, DM, SK, DSB), pp. 151–160.
REFSQ-2015-OliinykPSBS #case study #evaluation #industrial #metric #modelling: Metrics for the Evaluation of Feature Models in an Industrial Context: A Case Study at Opel (OO, KP, MS, MB, SS), pp. 33–48.
SAC-2015-JavedSBJ #robust: OR-PCA with dynamic feature selection for robust background subtraction (SJ, AS, TB, SKJ), pp. 86–91.
SAC-2015-MeftehBB #approach #case study #diagrams #evaluation #implementation #modelling #uml: Implementation and evaluation of an approach for extracting feature models from documented UML use case diagrams (MM, NB, HBA), pp. 1602–1609.
SLE-2015-OchoaRT #modelling #using: Using decision rules for solving conflicts in extended feature models (LO, OGR, TT), pp. 149–160.
CC-2015-St-AmourAF #profiling: Feature-Specific Profiling (VSA, LA, MF), pp. 49–68.
DAC-2015-JiangLZYW #effectiveness #image #performance: A 127 fps in full hd accelerator based on optimized AKAZE with efficiency and effectiveness for image feature extraction (GJ, LL, WZ, SY, SW), p. 6.
DATE-2015-BarraganL #case study #using: Feature selection for alternate test using wrappers: application to an RF LNA case study (MJB, GL), pp. 1229–1232.
DATE-2015-CaoBFCCAO #validation: LVS check for photonic integrated circuits: curvilinear feature extraction and validation (RC, JB, JF, LC, JC, AA, IO), pp. 1253–1256.
ICST-2015-ArcainiGV #detection #fault #generative #modelling #testing: Generating Tests for Detecting Faults in Feature Models (PA, AG, PV), pp. 1–10.
SIGMOD-2014-ZhangKR #optimisation: Materialization optimizations for feature selection workloads (CZ, AK, CR), pp. 265–276.
ICPC-2014-VasconcelosSW #visualisation: An information visualization feature model for supporting the selection of software visualizations (RV, MS, CW), pp. 122–125.
MSR-2014-PassosC #dataset #kernel #linux: A dataset of feature additions and feature removals from the Linux kernel (LTP, KC), pp. 376–379.
DUXU-DI-2014-HeZL #detection #fault #image #segmentation: Aluminum CT Image Defect Detection Based on Segmentation and Feature Extraction (NH, LZ, KL), pp. 446–454.
CIKM-2014-QianZ #clustering #multi #web: Unsupervised Feature Selection for Multi-View Clustering on Text-Image Web News Data (MQ, CZ), pp. 1963–1966.
CIKM-2014-WuHPZCZ #learning #multi: Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning (JW, ZH, SP, XZ, ZC, CZ), pp. 1699–1708.
ECIR-2014-NainiA #learning #rank: Exploiting Result Diversification Methods for Feature Selection in Learning to Rank (KDN, ISA), pp. 455–461.
ICML-c2-2014-JawanpuriaVN #kernel #learning #multi #on the: On p-norm Path Following in Multiple Kernel Learning for Non-linear Feature Selection (PJ, MV, JSN), pp. 118–126.
ICPR-2014-ChenYJ #analysis #linear #robust: An Improved Linear Discriminant Analysis with L1-Norm for Robust Feature Extraction (XC, JY, ZJ), pp. 1585–1590.
ICPR-2014-HuangZLW #distance: A Method of Discriminative Information Preservation and In-Dimension Distance Minimization Method for Feature Selection (SH, JZ, XL, LW), pp. 1615–1620.
ICPR-2014-KacheleZMS #quality #recognition #using: Prosodic, Spectral and Voice Quality Feature Selection Using a Long-Term Stopping Criterion for Audio-Based Emotion Recognition (MK, DZ, SM, FS), pp. 803–808.
ICPR-2014-LiewY #detection #novel #performance #robust: Generalized BRIEF: A Novel Fast Feature Extraction Method for Robust Hand Detection (CFL, TY), pp. 3014–3019.
ICPR-2014-RodriguesPPW #approach: A Binary Krill Herd Approach for Feature Selection (DR, LAMP, JPP, SATW), pp. 1407–1412.
ICPR-2014-TouaziMB #game studies: Feature Selection Scheme Based on Zero-Sum Two-Player Game (AT, FM, DB), pp. 1342–1347.
ICPR-2014-WenLWCW #classification #robust: Optimal Feature Selection for Robust Classification via l2, 1-Norms Regularization (JW, ZL, WKW, JC, MW), pp. 517–521.
ICPR-2014-YanJY #representation: Sparse Representation Preserving for Unsupervised Feature Selection (HY, ZJ, JY), pp. 1574–1578.
ICPR-2014-ZhangHLHZL #approach #hybrid: A Hybrid Feature Selection Approach by Correlation-Based Filters and SVM-RFE (JZ, XH, PPL, WH, YZ, HL), pp. 3684–3689.
ICPR-2014-ZhouZYL #polynomial #recognition: Improving Handwritten Chinese Character Recognition with Discriminative Quadratic Feature Extraction (MKZ, XYZ, FY, CLL), pp. 244–249.
KDD-2014-NguyenCRB #effectiveness: Effective global approaches for mutual information based feature selection (XVN, JC, SR, JB), pp. 512–521.
KDD-2014-PurushothamMKO #higher-order #interactive #learning #modelling: Factorized sparse learning models with interpretable high order feature interactions (SP, MRM, CCJK, RO), pp. 552–561.
KDD-2014-XuHWZ: Gradient boosted feature selection (ZEX, GH, KQW, AXZ), pp. 522–531.
SEKE-2014-LianZ #product line: An Evolutionary Methodology for Optimized Feature Selection in Software Product Lines (XL, LZ), pp. 63–66.
SEKE-2014-MaazounBB: Feature model recovery from product variants based on a cloning technique (JM, NB, HBA), pp. 431–436.
SEKE-2014-SalmanSD #clustering #information retrieval: Feature Location in a Collection of Product Variants: Combining Information Retrieval and Hierarchical Clustering (HES, AS, CD), pp. 426–430.
MoDELS-2014-Reinhartz-BergerFH #modelling: Comprehending Feature Models Expressed in CVL (IRB, KF, ØH), pp. 501–517.
SPLC-2014-BeucheS #modelling #variability: Managing variability with feature models (DB, MS), p. 364.
SPLC-2014-MennickeLSW #automation #petri net #process #verification #workflow: Automated verification of feature model configuration processes based on workflow Petri nets (SM, ML, JS, TW), pp. 62–71.
SPLC-2014-QuintonPBDB #consistency #evolution #modelling: Consistency checking for the evolution of cardinality-based feature models (CQ, AP, DLB, LD, GB), pp. 122–131.
SPLC-2014-SteinNC #multi: Preference-based feature model configuration with multiple stakeholders (JS, IN, EC), pp. 132–141.
SPLC-2014-YuZZJ #automation #case study #named: TDL: a transformation description language from feature model to use case for automated use case derivation (WY, WZ, HZ, ZJ), pp. 187–196.
RE-2014-LiuSYM14a #reasoning #requirements: Combined goal and feature model reasoning with the User Requirements Notation and jUCMNav (YL, YS, XY, GM), pp. 321–322.
RE-2014-SlavinLNB #diagrams #requirements #security #using: Managing security requirements patterns using feature diagram hierarchies (RS, JML, JN, TDB), pp. 193–202.
RE-2014-TranM #approach #evolution #nondeterminism: An Approach for Decision Support on the Uncertainty in Feature Model Evolution (LMST, FM), pp. 93–102.
RE-2014-ZhouLLLKL #requirements #towards #validation: Towards feature-oriented requirements validation for automotive systems (JZ, YL, KL, HL, DK, BL), pp. 428–436.
ASE-2014-Burke: Utilizing feature location techniques for feature addition and feature enhancement (JTB), pp. 879–882.
FSE-2014-BocovichA #interactive: Variable-specific resolutions for feature interactions (CB, JMA), pp. 553–563.
SAC-2014-AminikhanghahiWSSJ #effectiveness #smarttech: Effective tumor feature extraction for smart phone based microwave tomography breast cancer screening (SA, WW, SYS, SHS, SIJ), pp. 674–679.
SAC-2014-BergamascoN #3d #approach #retrieval #using: A new local feature extraction approach for content-based 3D medical model retrieval using shape descriptor (LCCB, FLSN), pp. 902–907.
SAC-2014-FerrazPG #symmetry: Feature description based on center-symmetric local mapped patterns (CTF, OPJ, AG), pp. 39–44.
GPCE-2014-RuprechtHL #automation #product line #scalability: Automatic feature selection in large-scale system-software product lines (AR, BH, DL), pp. 39–48.
SLE-2014-JaksicFCG #modelling #usability #visual notation: Evaluating the Usability of a Visual Feature Modeling Notation (AJ, RBF, PC, SG), pp. 122–140.
PDP-2014-RughettiSCQ #concurrent: Dynamic Feature Selection for Machine-Learning Based Concurrency Regulation in STM (DR, PdS, BC, FQ), pp. 68–75.
ICDAR-2013-AmaralFB #forensics #identification: Feature Selection for Forensic Handwriting Identification (AMMMA, COdAF, FB), pp. 922–926.
ICDAR-2013-BlucheNK #network #recognition #word: Feature Extraction with Convolutional Neural Networks for Handwritten Word Recognition (TB, HN, CK), pp. 285–289.
VLDB-2013-KondaKRS #data analysis #enterprise #using: Feature Selection in Enterprise Analytics: A Demonstration using an R-based Data Analytics System (PK, AK, CR, VS), pp. 1306–1309.
CSMR-2013-KazatoHKOOMHS #identification #incremental #source code: Incremental Feature Location and Identification in Source Code (HK, SH, TK, TO, SO, SM, TH, MS), pp. 371–374.
ICPC-2013-BassettK #retrieval: Structural information based term weighting in text retrieval for feature location (BB, NAK), pp. 133–141.
ICSM-2013-AlhindawiDCM #source code: Improving Feature Location by Enhancing Source Code with Stereotypes (NA, ND, MLC, JIM), pp. 300–309.
ICSM-2013-HillBBDLO #question: Which Feature Location Technique is Better? (EH, AB, DB, BD, DL, RO), pp. 408–411.
MSR-2013-IacobH #mobile #online: Retrieving and analyzing mobile apps feature requests from online reviews (CI, RH), pp. 41–44.
WCRE-2013-IshioHKO #automation #effectiveness #on the: On the effectiveness of accuracy of automated feature location technique (TI, SH, HK, TO), pp. 381–390.
CIKM-2013-FangZ #learning #multi: Discriminative feature selection for multi-view cross-domain learning (ZF, Z(Z), pp. 1321–1330.
ICML-c1-2013-0005LSL #learning #modelling #online: Online Feature Selection for Model-based Reinforcement Learning (TTN, ZL, TS, TYL), pp. 498–506.
ICML-c1-2013-KolarL #classification: Feature Selection in High-Dimensional Classification (MK, HL), pp. 329–337.
ICML-c1-2013-XiangTY #optimisation #performance: Efficient Sparse Group Feature Selection via Nonconvex Optimization (SX, XT, JY), pp. 284–292.
KDIR-KMIS-2013-WaadBL #algorithm #rank #search-based: Feature Selection by Rank Aggregation and Genetic Algorithms (BW, ABB, ML), pp. 74–81.
MLDM-2013-MinhAN #algorithm: DCA Based Algorithms for Feature Selection in Semi-supervised Support Vector Machines (LHM, LTHA, MCN), pp. 528–542.
MLDM-2013-StambaughYB: Analytic Feature Selection for Support Vector Machines (CS, HY, FB), pp. 219–233.
MLDM-2013-VavreckaL #classification: EEG Feature Selection Based on Time Series Classification (MV, LL), pp. 520–527.
RecSys-2013-KoenigsteinP #embedded #matrix #recommendation: Xbox movies recommendations: variational bayes matrix factorization with embedded feature selection (NK, UP), pp. 129–136.
SEKE-2013-PossompesDHT #generative #modelling: Model-Driven Generation of Context-Specific Feature Models (TP, CD, MH, CT), pp. 250–255.
SEKE-2013-WangKWN #case study #first-order #metric #statistics: A Study on First Order Statistics-Based Feature Selection Techniques on Software Metric Data (HW, TMK, RW, AN), pp. 467–472.
MoDELS-2013-WangGAL #automation #case study #industrial #testing #using: Automated Test Case Selection Using Feature Model: An Industrial Case Study (SW, AG, SA, ML), pp. 237–253.
PLEASE-2013-PatelGS #interactive #testing #variability: Feature interaction testing of variability intensive systems (SP, PG, VS), pp. 53–56.
SPLC-2013-Quinton0D #approach #constraints #modelling: Cardinality-based feature models with constraints: a pragmatic approach (CQ, DR, LD), pp. 162–166.
ECOOP-2013-OliveiraSLC #algebra #programming: Feature-Oriented Programming with Object Algebras (BCdSO, TvdS, AL, WRC), pp. 27–51.
SAC-PL-J-2011-AcherCLF13 #domain-specific language #modelling #named #scalability: FAMILIAR: A domain-specific language for large scale management of feature models (MA, PC, PL, RBF), pp. 657–681.
ASE-2013-PohlSP #complexity #modelling: Measuring the structural complexity of feature models (RP, VS, KP), pp. 454–464.
ASE-2013-ThungWLL #api #automation #recommendation: Automatic recommendation of API methods from feature requests (FT, SW, DL, JLL), pp. 290–300.
ESEC-FSE-2013-DavrilDHACH #scalability: Feature model extraction from large collections of informal product descriptions (JMD, ED, NH, MA, JCH, PH), pp. 290–300.
ICSE-2013-HenardPPKT #automation #modelling #testing #towards: Towards automated testing and fixing of re-engineered feature models (CH, MP, GP, JK, YLT), pp. 1245–1248.
ICSE-2013-WangPXZ #interactive #multi: Improving feature location practice with multi-faceted interactive exploration (JW, XP, ZX, WZ), pp. 762–771.
ICSE-2013-XingXJ #benchmark #kernel #metric #research #scalability: A large scale Linux-kernel based benchmark for feature location research (ZX, YX, SJ), pp. 1311–1314.
SAC-2013-AraujoGMSAB #approach #composition #modelling: Advanced modularity for building SPL feature models: a model-driven approach (JA, MG, AMDM, IS, VA, ELAB), pp. 1246–1253.
SAC-2013-BarreirosM #constraints #modelling: Configuration support for feature models with soft constraints (JB, AMDM), pp. 1307–1308.
SAC-2013-Jean-BaptisteMJA #adaptation #modelling #using: Modeling dynamic adaptations using augmented feature models (JBL, MTS, JMG, AB), pp. 1734–1741.
SAC-2013-Savoy: Feature selections for authorship attribution (JS), pp. 939–941.
DAC-2013-YuLJC #classification #detection #using: Machine-learning-based hotspot detection using topological classification and critical feature extraction (YTY, GHL, IHRJ, CC), p. 6.
FASE-2013-HaslingerLE #modelling #on the #set: On Extracting Feature Models from Sets of Valid Feature Combinations (ENH, RELH, AE), pp. 53–67.
ISSTA-2013-Thum #contract #product line #verification: Product-line verification with feature-oriented contracts (TT), pp. 374–377.
DocEng-2012-PenadesGC #documentation #modelling #workflow: Deriving document workflows from feature models (MdCP, AG, JHC), pp. 237–240.
CSMR-2012-KazatoHOMHS #concept analysis #multi: Feature Location for Multi-Layer System Based on Formal Concept Analysis (HK, SH, SO, SM, TH, MS), pp. 429–434.
ICPC-2012-DitMP: A TraceLab-based solution for creating, conducting, and sharing feature location experiments (BD, EM, DP), pp. 203–208.
ICPC-2012-KazatoHOMHS #towards: Toward structured location of features (HK, SH, SO, SM, TH, MS), pp. 255–256.
WCRE-2012-XueXJ: Feature Location in a Collection of Product Variants (YX, ZX, SJ), pp. 145–154.
WCRE-2012-ZiftciK #data mining #mining #using: Feature Location Using Data Mining on Existing Test-Cases (CZ, IK), pp. 155–164.
CAiSE-2012-AcherHCQLM #difference: Feature Model Differences (MA, PH, PC, CQ, PL, PM), pp. 629–645.
CAiSE-2012-EnsanBG #generative #modelling #product line #search-based #testing: Evolutionary Search-Based Test Generation for Software Product Line Feature Models (FE, EB, DG), pp. 613–628.
CIKM-2012-AhmedADSA #behaviour #multi: Web-scale multi-task feature selection for behavioral targeting (AA, MA, AD, AJS, TA), pp. 1737–1741.
CIKM-2012-CamposBDC #identification: Time feature selection for identifying active household members (PGC, AB, FD, IC), pp. 2311–2314.
CIKM-2012-WangZLL #categorisation: Feature selection based on term frequency and T-test for text categorization (DW, HZ, RL, WL), pp. 1482–1486.
CIKM-2012-ZhuYCQ #approach #classification #graph: Graph classification: a diversified discriminative feature selection approach (YZ, JXY, HC, LQ), pp. 205–214.
ICML-2012-DanylukA #probability: Feature Selection via Probabilistic Outputs (APD, NA), p. 127.
ICML-2012-Zhu #modelling #parametricity #predict: Max-Margin Nonparametric Latent Feature Models for Link Prediction (JZ), p. 154.
ICPR-2012-0007B #classification #image #kernel #multi: Multiple local kernel integrated feature selection for image classification (YS, BB), pp. 2230–2233.
ICPR-2012-AiDHC #analysis #component #independence #multi: Multiple feature selection and fusion based on generalized N-dimensional independent component analysis (DA, GD, XHH, YWC), pp. 971–974.
ICPR-2012-AyechZ #clustering #image #modelling #segmentation #statistics: Terahertz image segmentation based on K-harmonic-means clustering and statistical feature extraction modeling (MWA, DZ), pp. 222–225.
ICPR-2012-BeinruckerDB: Early stopping for mutual information based feature selection (AB, UD, GB), pp. 975–978.
ICPR-2012-GutmannH #architecture #image #learning: Learning a selectivity-invariance-selectivity feature extraction architecture for images (MG, AH), pp. 918–921.
ICPR-2012-HidoM #predict: Temporal feature selection for time-series prediction (SH, TM), pp. 3557–3560.
ICPR-2012-HuangLC #clustering #kernel #multi #self: Cluster-dependent feature selection by multiple kernel self-organizing map (KCH, YYL, JZC), pp. 589–592.
ICPR-2012-JensenED #classification: Classification of kinematic golf putt data with emphasis on feature selection (UJ, BE, FD), pp. 1735–1738.
ICPR-2012-KunchevaF #detection #multi #streaming: PCA feature extraction for change detection in multidimensional unlabelled streaming data (LIK, WJF), pp. 1140–1143.
ICPR-2012-LeiLL #analysis #linear #performance #recognition: Efficient feature selection for linear discriminant analysis and its application to face recognition (ZL, SL, SZL), pp. 1136–1139.
ICPR-2012-LiuSZ #graph: Sparsity Score: A new filter feature selection method based on graph (ML, DS, DZ), pp. 959–962.
ICPR-2012-LiuW12a #kernel: Unsupervised discriminative feature selection in a kernel space via L2, 1-norm minimization (YL, YW), pp. 1205–1208.
ICPR-2012-MiaoLZ #fault #predict: Cost-sensitive feature selection with application in software defect prediction (LM, ML, DZ), pp. 967–970.
ICPR-2012-WangAG #adaptation #graph #matrix: Adaptive graph regularized Nonnegative Matrix Factorization via feature selection (JW, IA, XG), pp. 963–966.
ICPR-2012-WangSCPZ #analysis #component #named: STPCA: Sparse tensor Principal Component Analysis for feature extraction (SW, MS, YHC, EPP, CZ), pp. 2278–2281.
ICPR-2012-WangST #linear #programming #recognition #robust: Robust regularized feature selection for iris recognition via linear programming (LW, ZS, TT), pp. 3358–3361.
ICPR-2012-ZhangH #recognition #using: Face recognition using semi-supervised spectral feature selection (ZZ, ERH), pp. 1294–1297.
ICPR-2012-ZhangH12a #recognition: Unsupervised spectral feature selection for face recognition (ZZ, ERH), pp. 1787–1790.
ICPR-2012-ZhangLGZ #classification: An improved EEMD model for feature extraction and classification of gunshot in public places (ZZ, WL, WG, JZ), pp. 1517–1520.
ICPR-2012-ZhangWBZCZ #detection: Object detection via foreground contour feature selection and part-based shape model (HZ, JW, XB, JZ, JC, HZ), pp. 2524–2527.
ICPR-2012-ZhangWN #detection #student: Bayesian feature selection and model detection for student’s t-mixture distributions (HZ, QMJW, TMN), pp. 1631–1634.
KDD-2012-TangL #social #social media: Unsupervised feature selection for linked social media data (JT, HL), pp. 904–912.
KDD-2012-WoznicaNK #mining #robust: Model mining for robust feature selection (AW, PN, AK), pp. 913–921.
KDD-2012-YuDSW #mining #streaming: Mining emerging patterns by streaming feature selection (KY, WD, DAS, XW), pp. 60–68.
MLDM-2012-StaroszczykOM #analysis #comparative #recognition: Comparative Analysis of Feature Selection Methods for Blood Cell Recognition in Leukemia (TS, SO, TM), pp. 467–481.
SEKE-2012-GaoKN #metric: Stability of Filter-Based Feature Selection Methods for Imbalanced Software Measurement Data (KG, TMK, AN), pp. 74–79.
SEKE-2012-ShenHTGZ #logic #modelling #verification: Feature modeling and Verification based on Description Logics (GS, ZH, CT, QG, WZ), pp. 422–425.
MoDELS-2012-AranegaEM #model transformation #using: Using Feature Model to Build Model Transformation Chains (VA, AE, SM), pp. 562–578.
MoDELS-2012-SchroeterLW #modelling #multi: Multi-perspectives on Feature Models (JS, ML, TW), pp. 252–268.
PLEASE-2012-AcherMHCL #modelling #tool support: Languages and tools for managing feature models (MA, RM, PH, PC, PL), pp. 25–28.
PLEASE-2012-QuintonDHMC #modelling #using: Using feature modelling and automations to select among cloud solutions (CQ, LD, PH, SM, EC), pp. 17–20.
SPLC-2012-AndersenCSW #modelling #performance #synthesis: Efficient synthesis of feature models (NA, KC, SS, AW), pp. 106–115.
SPLC-2012-BragaJBL #certification #modelling #product line: Incorporating certification in feature modelling of an unmanned aerial vehicle product line (RTVB, OTJ, KRLJCB, JL), pp. 249–258.
SPLC-2012-El-SharkawyDS #analysis #modelling: From feature models to decision models and back again an analysis based on formal transformations (SES, SD, KS), pp. 126–135.
SPLC-2012-HofmanSPKB #modelling #product line: Domain specific feature modeling for software product lines (PH, TS, TP, MK, AB), pp. 229–238.
SPLC-2012-JohansenHF #algorithm #array #generative #modelling #scalability: An algorithm for generating t-wise covering arrays from large feature models (MFJ, ØH, FF), pp. 46–55.
SPLC-2012-SoltaniAGHB #automation #non-functional #requirements: Automated planning for feature model configuration based on functional and non-functional requirements (SS, MA, DG, MH, EB), pp. 56–65.
RE-2012-AroraSR #interactive #nondeterminism: Resolving uncertainty in automotive feature interactions (SA, PS, SR), pp. 21–30.
RE-2012-LiZ0 #configuration management #modelling #named: MbFM: A matrix-based tool for modeling and configuring feature models (LL, HZ, WZ), pp. 325–326.
RE-2012-ShakerAW #modelling #requirements: A feature-oriented requirements modelling language (PS, JMA, SW), pp. 151–160.
RE-2012-Yi0ZJM #constraints #mining #modelling: Mining binary constraints in the construction of feature models (LY, WZ, HZ, ZJ, HM), pp. 141–150.
RE-2012-YiZ0J #collaboration #modelling #named: CoFM: An environment for collaborative feature modeling (LY, HZ, WZ, ZJ), pp. 317–318.
ICSE-2012-OuelletMSG: Locating features in dynamically configured avionics software (MO, EM, NS, MG), pp. 1453–1454.
GPCE-2012-RysselPK #modelling #reasoning: Reasoning of feature models from derived features (UR, JP, KK), pp. 21–30.
CASE-2012-Chang #detection #fault #process #using: Fault detection for plasma-enhanced chemical vapor deposition process using feature extraction (YJC), pp. 491–496.
FASE-2012-ThumSKAS #contract #design #programming: Applying Design by Contract to Feature-Oriented Programming (TT, IS, MK, SA, GS), pp. 255–269.
ECSA-2011-AcherCCMDL #architecture #modelling #reverse engineering: Reverse Engineering Architectural Feature Models (MA, AC, PC, PM, LD, PL), pp. 220–235.
ECSA-2011-GamezFA #architecture #modelling: Autonomic Computing Driven by Feature Models and Architecture in FamiWare (NG, LF, MAA), pp. 164–179.
DRR-2011-FanSNMH #recognition: Natural scene logo recognition by joint boosting feature selection in salient regions (WF, JS, SN, AM, YH), pp. 1–10.
ICDAR-2011-AlmazanFV #recognition: A Non-rigid Feature Extraction Method for Shape Recognition (JA, AF, EV), pp. 987–991.
ICDAR-2011-ChaabouniBKAA11a #identification #online: Combining of Off-line and On-line Feature Extraction Approaches for Writer Identification (AC, HB, MK, AMA, HEA), pp. 1299–1303.
ICDAR-2011-LouradourK #categorisation #documentation #image #performance: Sample-Dependent Feature Selection for Faster Document Image Categorization (JL, CK), pp. 309–313.
ICDAR-2011-NguyenB #2d #verification: An Application of the 2D Gaussian Filter for Enhancing Feature Extraction in Off-line Signature Verification (VN, MB), pp. 339–343.
ICDAR-2011-ParodiGB #approach #invariant #verification: A Circular Grid-Based Rotation Invariant Feature Extraction Approach for Off-line Signature Verification (MP, JCG, AB), pp. 1289–1293.
ICDAR-2011-VinelDA #linear #optimisation #random: Joint Optimization of Hidden Conditional Random Fields and Non Linear Feature Extraction (AV, TMTD, TA), pp. 513–517.
ICPC-2011-DitGPA #identifier #question: Can Better Identifier Splitting Techniques Help Feature Location? (BD, LG, DP, GA), pp. 11–20.
ICPC-2011-JurgensFHDVP #evolution #profiling: Feature Profiling for Evolving Systems (EJ, MF, MH, FD, RV, KHP), pp. 171–180.
ICSM-2011-WangPXZ #case study #process: An exploratory study of feature location process: Distinct phases, recurring patterns, and elementary actions (JW, XP, ZX, WZ), pp. 213–222.
WCRE-2011-HaslingerLE #modelling #reverse engineering #set #source code: Reverse Engineering Feature Models from Programs’ Feature Sets (ENH, RELH, AE), pp. 308–312.
ICEIS-v1-2011-MasadaSO #clustering #documentation #string: Documents as a Bag of Maximal Substrings — An Unsupervised Feature Extraction for Document Clustering (TM, YS, KO), pp. 5–13.
ICEIS-v3-2011-XiongNF #component #composition #research: Research on Component Composition based on Feature Model (LRX, ZN, JF), pp. 214–222.
CIKM-2011-BanerjeeC #distributed #privacy #using: Privacy preserving feature selection for distributed data using virtual dimension (MB, SC), pp. 2281–2284.
CIKM-2011-GuH #network #towards: Towards feature selection in network (QG, JH), pp. 1175–1184.
CIKM-2011-GuLH #correlation #multi: Correlated multi-label feature selection (QG, ZL, JH), pp. 1087–1096.
CIKM-2011-LiuWZ #clustering #using: Feature selection using hierarchical feature clustering (HL, XW, SZ), pp. 979–984.
CIKM-2011-TariqK #performance: Fast supervised feature extraction by term discrimination information pooling (AT, AK), pp. 2233–2236.
ECIR-2011-JagarlamudiB #similarity: Fractional Similarity: Cross-Lingual Feature Selection for Search (JJ, PNB), pp. 226–237.
ECIR-2011-NeumayerMN #categorisation: Combination of Feature Selection Methods for Text Categorisation (RN, RM, KN), pp. 763–766.
ICML-2011-GuanDJ #probability: A Unified Probabilistic Model for Global and Local Unsupervised Feature Selection (YG, JGD, MIJ), pp. 1073–1080.
ICML-2011-JiangR: Eigenvalue Sensitive Feature Selection (YJ, JR), pp. 89–96.
ICML-2011-RifaiVMGB: Contractive Auto-Encoders: Explicit Invariance During Feature Extraction (SR, PV, XM, XG, YB), pp. 833–840.
KDIR-2011-DoquireV #approach #category theory #hybrid: An Hybrid Approach to Feature Selection for Mixed Categorical and Continuous Data (GD, MV), pp. 394–401.
KDIR-2011-GilliesSPW #ontology #simulation: Gene Ontology based Simulation for Feature Selection (CEG, MRS, NVP, GDW), pp. 294–302.
KDIR-2011-HagenauLN #predict: Impact of Feature Selection and Feature Types on Financial Stock Price Prediction (MH, ML, DN), pp. 303–308.
SEKE-2011-PossompesDHT #design #diagrams #implementation #uml: Design of a UML profile for feature diagrams and its tooling implementation (TP, CD, MH, CT), pp. 693–698.
SEKE-2011-ReformatP #approach #evaluation: Criteria of Human Software Evaluation: Feature Selection Approach (MR, SP), pp. 71–76.
SIGIR-2011-GengLWWS #assessment #quality #statistics #web: Statistical feature extraction for cross-language web content quality assessment (GG, XL, LMW, WW, SS), pp. 1129–1130.
SIGIR-2011-JinY #classification #image #multi: Integrating hierarchical feature selection and classifier training for multi-label image annotation (CJ, CY), pp. 515–524.
MoDELS-2011-JohansenHF #combinator #modelling #product line #testing: Properties of Realistic Feature Models Make Combinatorial Testing of Product Lines Feasible (MFJ, ØH, FF), pp. 638–652.
PLEASE-2011-SunCGW #approach #using: Supporting feature model configuration using a demonstration-based approach (YS, HC, JGG, JW), pp. 55–59.
SPLC-2011-KatoY #cumulative #interactive #product line: Variation Management for Software Product Lines with Cumulative Coverage of Feature Interactions (SK, NY), pp. 140–149.
SPLC-2011-Lopez-HerrejonME #case study #refactoring #requirements: From Requirements to Features: An Exploratory Study of Feature-Oriented Refactoring (RELH, LMM, AE), pp. 181–190.
SPLC-2011-ThumKES #modelling: Abstract Features in Feature Modeling (TT, CK, SE, NS), pp. 191–200.
SPLC-2011-ThurimellaJ #plugin: Metadoc Feature Modeler: A Plug-in for IBM Rational DOORS (AKT, DJ), pp. 313–322.
RE-2011-FitzgeraldLF #predict: Early failure prediction in feature request management systems (CF, EL, AF), pp. 229–238.
ASE-2011-AcherCLF #modelling #slicing: Slicing feature models (MA, PC, PL, RBF), pp. 424–427.
ASE-2011-AcherCLF11a #modelling: Decomposing feature models: language, environment, and applications (MA, PC, PL, RBF), pp. 600–603.
ASE-2011-ApelSWRB #detection #interactive #using #verification: Detection of feature interactions using feature-aware verification (SA, HS, PW, AvR, DB), pp. 372–375.
ASE-2011-PohlLP #algorithm #analysis #automation #comparison #modelling #performance: A performance comparison of contemporary algorithmic approaches for automated analysis operations on feature models (RP, KL, KP), pp. 313–322.
ASE-2011-SoltaniAHGB #automation: Automated planning for feature model configuration based on stakeholders’ business concerns (SS, MA, MH, DG, EB), pp. 536–539.
GTTSE-2011-KastnerA #development: Feature-Oriented Software Development (CK, SA), pp. 346–382.
ICSE-2011-CataldoH #analysis #development #empirical #integration: Factors leading to integration failures in global feature-oriented development: an empirical analysis (MC, JDH), pp. 161–170.
ICSE-2011-PengXTYZ: Iterative context-aware feature location (XP, ZX, XT, YY, WZ), pp. 900–903.
ICSE-2011-SheLBWC #modelling #reverse engineering: Reverse engineering feature models (SS, RL, TB, AW, KC), pp. 461–470.
ICSE-2011-StengelFAFKD #development #infinity #interface: View infinity: a zoomable interface for feature-oriented software development (MS, MF, SA, JF, CK, RD), pp. 1031–1033.
SAC-2011-AcherCLF #domain-specific language #modelling: A domain-specific language for managing feature models (MA, PC, PL, RBF), pp. 1333–1340.
SAC-2011-EbraertSJ #design #diagrams #implementation: Change-based FODA diagrams: bridging the gap between feature-oriented design and implementation (PE, QDS, DJ), pp. 1345–1352.
SAC-2011-HuMB #clustering #documentation #interactive: Interactive feature selection for document clustering (YH, EEM, JB), pp. 1143–1150.
SAC-2011-LargeronMG #categorisation: Entropy based feature selection for text categorization (CL, CM, MG), pp. 924–928.
GPCE-2011-BatoryHK #composition #interactive: Feature interactions, products, and composition (DSB, PH, JK), pp. 13–22.
CASE-2011-SenoussiCDZ #detection #fault #process: Feature selection for fault detection systems: Application to the Tennessee Eastman Process (HS, BCM, MD, NZ), pp. 189–194.
DAC-2011-ClemonsJPSA #embedded #named: EFFEX: an embedded processor for computer vision based feature extraction (JC, AJ, RP, SS, TMA), pp. 1020–1025.
CBSE-2010-EichbergKMM #component #composition #modelling #using: Component Composition Using Feature Models (ME, KK, RM, MM), pp. 200–215.
DocEng-2010-KarolHHA #documentation #modelling #product line #using: Using feature models for creating families of documents (SK, MH, FH, UA), pp. 259–262.
DocEng-2010-NamaneSM #matrix #recognition #using: Degraded dot matrix character recognition using CSM-based feature extraction (AN, EHS, PM), pp. 207–210.
DRR-2010-OhL #evaluation #optimisation #recognition: Ant colony optimization with selective evaluation for feature selection in character recognition (ISO, JSL), pp. 1–10.
ICPC-2010-ChenR #case study #dependence #graph #using: Case Study of Feature Location Using Dependence Graph, after 10 Years (KC, VR), pp. 1–3.
ICPC-2010-RevelleDP #data fusion #mining #using #web: Using Data Fusion and Web Mining to Support Feature Location in Software (MR, BD, DP), pp. 14–23.
CIKM-2010-DingSBVWLC #automation #detection #embedded #framework #image #using: Automatic detection of craters in planetary images: an embedded framework using feature selection and boosting (WD, TFS, LPCB, RV, YW, ZL, TC), pp. 749–758.
CIKM-2010-FeiQH: Regularization and feature selection for networked features (HF, BQ, JH), pp. 1893–1896.
CIKM-2010-LiuXCY #classification #multi: Orientation distance-based discriminative feature extraction for multi-class classification (BL, YX, LC, PSY), pp. 909–918.
CIKM-2010-YangKL #learning #multi #online: Online learning for multi-task feature selection (HY, IK, MRL), pp. 1693–1696.
ICML-2010-GaudelS #game studies: Feature Selection as a One-Player Game (RG, MS), pp. 359–366.
ICML-2010-MasaeliFD #reduction: From Transformation-Based Dimensionality Reduction to Feature Selection (MM, GF, JGD), pp. 751–758.
ICML-2010-PetrikTPZ #approximate #linear #markov #process #source code #using: Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes (MP, GT, RP, SZ), pp. 871–878.
ICML-2010-TanWT #dataset #learning: Learning Sparse SVM for Feature Selection on Very High Dimensional Datasets (MT, LW, IWT), pp. 1047–1054.
ICML-2010-WuYWD #online #streaming: Online Streaming Feature Selection (XW, KY, HW, WD), pp. 1159–1166.
ICPR-2010-AdamsWDMBG #less is more #recognition: Genetic-Based Type II Feature Extraction for Periocular Biometric Recognition: Less is More (JA, DLW, GVD, PEM, KSB, GG), pp. 205–208.
ICPR-2010-BonevEGB #graph: Information-theoretic Feature Selection from Unattributed Graphs (BB, FE, DG, SB), pp. 930–933.
ICPR-2010-CakirC #2d #image #using: Image Feature Extraction Using 2D Mel-Cepstrum (SÇ, AEÇ), pp. 674–677.
ICPR-2010-ColemanSG #architecture #using: Coarse Scale Feature Extraction Using the Spiral Architecture Structure (SAC, BWS, BG), pp. 2370–2373.
ICPR-2010-DukkipatiYM #classification #modelling: Maximum Entropy Model Based Classification with Feature Selection (AD, AKY, MNM), pp. 565–568.
ICPR-2010-EkbalSG #multi #optimisation #recognition #using: Feature Selection Using Multiobjective Optimization for Named Entity Recognition (AE, SS, CSG), pp. 1937–1940.
ICPR-2010-InoueSSF #modelling #using: High-Level Feature Extraction Using SIFT GMMs and Audio Models (NI, TS, KS, SF), pp. 3220–3223.
ICPR-2010-LaiJYW: Sparse Local Discriminant Projections for Feature Extraction (ZL, ZJ, JY, WKW), pp. 926–929.
ICPR-2010-Parker #classification #empirical: An Empirical Study of Feature Extraction Methods for Audio Classification (CP), pp. 4593–4596.
ICPR-2010-SakarK #analysis #canonical #correlation #hybrid: A Hybrid Method for Feature Selection Based on Mutual Information and Canonical Correlation Analysis (COS, OK), pp. 4360–4363.
ICPR-2010-SakarKSG #clustering #predict: Prediction of Protein Sub-nuclear Location by Clustering mRMR Ensemble Feature Selection (COS, OK, HS, FG), pp. 2572–2575.
ICPR-2010-SomolGP #algorithm #problem #set: The Problem of Fragile Feature Subset Preference in Feature Selection Methods and a Proposal of Algorithmic Workaround (PS, JG, PP), pp. 4396–4399.
ICPR-2010-StuhlsatzLZ #classification: Feature Extraction for Simple Classification (AS, JL, TZ), pp. 1525–1528.
ICPR-2010-WanLJ: Feature Extraction Based on Class Mean Embedding (CME) (MW, ZL, ZJ), pp. 4174–4177.
ICPR-2010-YangK #fourier #performance: Fast Polar and Spherical Fourier Descriptors for Feature Extraction (ZY, SiK), pp. 975–978.
ICPR-2010-YangZZZ #novel #recognition #representation: Monogenic Binary Pattern (MBP): A Novel Feature Extraction and Representation Model for Face Recognition (MY, LZ, LZ, DZ), pp. 2680–2683.
ICPR-2010-Yildiz: Feature Extraction from Discrete Attributes (OTY), pp. 3915–3918.
ICPR-2010-ZhaoHDC #3d #automation #recognition #statistics: Automatic 3D Facial Expression Recognition Based on a Bayesian Belief Net and a Statistical Facial Feature Model (XZ, DH, ED, LC), pp. 3724–3727.
ICPR-2010-ZhaoWSS #process #recognition: Motif Discovery and Feature Selection for CRF-based Activity Recognition (LZ, XW, GS, RS), pp. 3826–3829.
KDD-2010-CaiZH #clustering #multi: Unsupervised feature selection for multi-cluster data (DC, CZ, XH), pp. 333–342.
KDD-2010-KongY #classification #graph: Semi-supervised feature selection for graph classification (XK, PSY), pp. 793–802.
KDD-2010-YangO #predict #probability #using: Feature selection for support vector regression using probabilistic prediction (JBY, CJO), pp. 343–352.
KDD-2010-YuHW #clustering #documentation #process: Document clustering via dirichlet process mixture model with feature selection (GY, RzH, ZW), pp. 763–772.
KDD-2010-ZhuLX #incremental #learning #markov #named #performance #random: Grafting-light: fast, incremental feature selection and structure learning of Markov random fields (JZ, NL, EPX), pp. 303–312.
KDIR-2010-PalmeriniRMCV: Feature Selection for the Instrumented Timed Up and Go in Parkinson’s Disease (LP, LR, SM, LC, FV), pp. 95–99.
KDIR-2010-SiebersS: Interleaving Forward Backward Feature Selection (MS, US), pp. 454–457.
SEKE-2010-Abu-MatarGKE #architecture #modelling #variability: Feature Modeling for Service Variability Management in Service-Oriented Architectures (MAM, HG, MK, AME), pp. 468–473.
SEKE-2010-WangKG #classification #quality: Ensemble Feature Selection Technique for Software Quality Classification (HW, TMK, KG), pp. 215–220.
ECMFA-2010-AcherCLF #composition: Comparing Approaches to Implement Feature Model Composition (MA, PC, PL, RBF), pp. 3–19.
MoDELS-v1-2010-WangXHZZM #approach #consistency #modelling: A Dynamic-Priority Based Approach to Fixing Inconsistent Feature Models (BW, YX, ZH, HZ, WZ, HM), pp. 181–195.
SPLC-2010-BagheriNRG #configuration management #modelling #product line #requirements: Configuring Software Product Line Feature Models Based on Stakeholders’ Soft and Hard Requirements (EB, TDN, AR, DG), pp. 16–31.
SPLC-2010-CosmoZ #dependence #diagrams: Feature Diagrams as Package Dependencies (RDC, SZ), pp. 476–480.
SPLC-2010-GhanamM #execution #modelling #testing #using: Linking Feature Models to Code Artifacts Using Executable Acceptance Tests (YG, FM), pp. 211–225.
SPLC-2010-GilKM #constraints #diagrams #modelling: Sans Constraints? Feature Diagrams vs. Feature Models (JYG, SKD, IM), pp. 271–285.
SPLC-2010-GuoW #consistency #evolution #modelling #towards: Towards Consistent Evolution of Feature Models (JG, YW), pp. 451–455.
SPLC-2010-KaratasOD #constraints #finite #logic programming #modelling: Mapping Extended Feature Models to Constraint Logic Programming over Finite Domains (ASK, HO, AHD), pp. 286–299.
SPLC-2010-LeeK: Usage Context as Key Driver for Feature Selection (KL, KCK), pp. 32–46.
SPLC-2010-Nakajima #automation #diagrams #encoding: Non-clausal Encoding of Feature Diagram for Automated Diagnosis (SN), pp. 420–424.
SPLC-2010-YoshimuraAF #constraints #identification #mining: A Method to Identify Feature Constraints Based on Feature Selections Mining (KY, YA, TF), pp. 425–429.
SPLC-2010-ZhangJ #approach #hybrid #programming: A Hybrid Approach to Feature-Oriented Programming in XVCL (HZ, SJ), pp. 440–445.
ASE-2010-RatanotayanonCS #transitive #using: Using transitive changesets to support feature location (SR, HJC, SES), pp. 341–344.
FSE-2010-Elkhodary #adaptation #approach #self: A learning-based approach for engineering feature-oriented self-adaptive software systems (AME), pp. 345–348.
ICSE-2010-SavageRP #named: FLAT³: feature location and textual tracing tool (TS, MR, DP), pp. 255–258.
ICSE-2010-Shaker #modelling #requirements: Feature-oriented requirements modelling (PS), pp. 365–368.
SAC-2010-BaccianellaES: Feature selection for ordinal regression (SB, AE, FS), pp. 1748–1754.
SAC-2010-EbraertDMJ: Intensional changes: modularizing crosscutting features (PE, TD, TM, DJ), pp. 2176–2182.
SAC-2010-Nakajima #automation #diagrams: Semi-automated diagnosis of FODA feature diagram (SN), pp. 2191–2197.
SAC-2010-Sobernig #interactive #network: Feature interaction networks (SS), pp. 2360–2364.
GPCE-2010-SchulzeAK #product line: Code clones in feature-oriented software product lines (SS, SA, CK), pp. 103–112.
SLE-2010-HubauxBHMH #case study #industrial #modelling: Evaluating a Textual Feature Modelling Language: Four Industrial Case Studies (AH, QB, HH, RM, PH), pp. 337–356.
DATE-2010-RathiDGCV #distance #gpu #implementation: A GPU based implementation of Center-Surround Distribution Distance for feature extraction and matching (AR, MD, WG, RTC, NV), pp. 172–177.
ICST-2010-SeguraHBR #analysis #approach #automation #generative #modelling #testing: Automated Test Data Generation on the Analyses of Feature Models: A Metamorphic Testing Approach (SS, RMH, DB, ARC), pp. 35–44.
WICSA-ECSA-2009-PerovichRB #architecture #product line: Feature model to product architectures: Applying MDE to Software Product Lines (DP, POR, MCB), pp. 201–210.
ICDAR-2009-ChouaibVCT #documentation: Generic Feature Selection and Document Processing (HC, NV, FC, ST), pp. 356–360.
ICDAR-2009-LecerfC #documentation #scalability: Scalable Feature Extraction from Noisy Documents (LL, BC), pp. 361–365.
ICDAR-2009-VamvakasGP #classification #documentation #novel #recognition: A Novel Feature Extraction and Classification Methodology for the Recognition of Historical Documents (GV, BG, SJP), pp. 491–495.
ICDAR-2009-WakabayashiPKM #recognition: F-ratio Based Weighted Feature Extraction for Similar Shape Character Recognition (TW, UP, FK, YM), pp. 196–200.
ICDAR-2009-ZhuSMHN #classification: Separate Chinese Character and English Character by Cascade Classifier and Feature Selection (YZ, JS, AM, YH, SN), pp. 1191–1195.
ICPC-2009-EdwardsWSG: Instrumenting time-sensitive software for feature location (DE, NW, SS, EG), pp. 130–137.
ICPC-2009-RevelleP #case study: An exploratory study on assessing feature location techniques (MR, DP), pp. 218–222.
ICSM-2009-GeetD #case study #cobol #experience: Feature location in COBOL mainframe systems: An experience report (JVG, SD), pp. 361–370.
WCRE-1999-YangPZ99a #concept analysis #data access #multi #semantics #using: Domain Feature Model Recovery from Multiple Applications Using Data Access Semantics and Formal Concept Analysis (YY, XP, WZ), pp. 215–224.
HCI-NT-2009-AsteriadisKK #human-computer: Feature Extraction and Selection for Inferring User Engagement in an HCI Environment (SA, KK, SDK), pp. 22–29.
HIMI-DIE-2009-SrinivasSPK #classification #performance #using: Efficient Text Classification Using Best Feature Selection and Combination of Methods (MS, KPS, EVP, SAK), pp. 437–446.
CIKM-2009-PanCASD #ranking #using: Feature selection for ranking using boosted trees (FP, TC, DA, FS, GD), pp. 2025–2028.
CIKM-2009-XuFZH #orthogonal #using: To obtain orthogonal feature extraction using training data selection (YX, SF, JZ, OH), pp. 1819–1822.
ICML-2009-DiukLL #adaptation #learning #problem: The adaptive k-meteorologists problem and its application to structure learning and feature selection in reinforcement learning (CD, LL, BRL), pp. 249–256.
ICML-2009-HelleputteD #linear #modelling: Partially supervised feature selection with regularized linear models (TH, PD), pp. 409–416.
ICML-2009-KolterN09a #difference #learning: Regularization and feature selection in least-squares temporal difference learning (JZK, AYN), pp. 521–528.
ICML-2009-XuJYLK: Non-monotonic feature selection (ZX, RJ, JY, MRL, IK), pp. 1145–1152.
ICML-2009-YuanH #learning #robust: Robust feature extraction via information theoretic learning (XY, BGH), pp. 1193–1200.
KDD-2009-LoscalzoYD: Consensus group stable feature selection (SL, LY, CHQD), pp. 567–576.
MLDM-2009-JingWYX #categorisation #framework: A General Framework of Feature Selection for Text Categorization (HJ, BW, YY, YX), pp. 647–662.
SEKE-2009-LinWK #algorithm #hybrid #novel: A Novel Hybrid Search Algorithm for Feature Selection (PL, HW, TMK), pp. 81–86.
SEKE-2009-Nakajima #diagrams: Constructing FODA Feature Diagrams with a GUI-based Tool (SN), pp. 20–25.
SIGIR-2009-PunithaJG #automation #multi #query #retrieval #topic #using #video: Topic prerogative feature selection using multiple query examples for automatic video retrieval (PP, JMJ, AG), pp. 804–805.
SIGIR-2009-YangC #automation #induction #taxonomy: Feature selection for automatic taxonomy induction (HY, JC), pp. 684–685.
SPLC-2009-Fernandez-AmorosGS #diagrams #modelling #product line: Inferring information from feature diagrams to product line economic models (DFA, RHG, JACS), pp. 41–50.
SPLC-2009-HartmannTM #independence #modelling: Supplier independent feature modelling (HH, TT, AAJM), pp. 191–200.
SPLC-2009-HubauxCH #formal method #modelling #workflow: Formal modelling of feature configuration workflows (AH, AC, PH), pp. 221–230.
SPLC-2009-MendoncaWC #analysis #modelling #satisfiability: SAT-based analysis of feature models is easy (MM, AW, KC), pp. 231–240.
SPLC-2009-TunBCHH #approach #requirements: Relating requirements and feature configurations: a systematic approach (TTT, QB, AC, AH, PH), pp. 201–210.
SPLC-2009-WestonCR #composition #framework #modelling #natural language #requirements #semantics: A framework for constructing semantically composable feature models from natural language requirements (NW, RC, AR), pp. 211–220.
SPLC-2009-WhiteDSB #automation #multi #problem #reasoning: Automated reasoning for multi-step feature model configuration problems (JW, BD, DCS, DB), pp. 11–20.
RE-2009-ClassenHH #analysis #workflow: Analysis of Feature Configuration Workflows (AC, AH, PH), pp. 381–382.
RE-2009-SalinesiRDM #classification #fault #modelling #product line #towards #verification: Looking for Product Line Feature Models Defects: Towards a Systematic Classification of Verification Criteria (CS, CR, DD, RM), pp. 385–386.
RE-2009-WaldmannJ #perspective #requirements #reuse: Feature-oriented Requirements Satisfy Needs for Reuse and Systems View (BW, PJ), pp. 329–334.
RE-2009-WangZZJM #approach #case study #modelling: A Use Case Based Approach to Feature Models’ Construction (BW, WZ, HZ, ZJ, HM), pp. 121–130.
ICSE-2009-KastnerTSFLWA #development #framework #named: FeatureIDE: A tool framework for feature-oriented software development (CK, TT, GS, JF, TL, FW, SA), pp. 611–614.
ICSE-2009-ThumBK #modelling #reasoning: Reasoning about edits to feature models (TT, DSB, CK), pp. 254–264.
SAC-2009-ZaidKT #modelling #semantics #web: Applying semantic web technology to feature modeling (LAZ, FK, ODT), pp. 1252–1256.
GPCE-2009-SanenTJ #approach #interactive #problem: Mapping problem-space to solution-space features: a feature interaction approach (FS, ET, WJ), pp. 167–176.
SLE-2009-AcherCLF #modelling: Composing Feature Models (MA, PC, PL, RBF), pp. 62–81.
FASE-2009-NguyenNPAN #clone detection #detection #performance: Accurate and Efficient Structural Characteristic Feature Extraction for Clone Detection (HAN, TTN, NHP, JMAK, TNN), pp. 440–455.
ECSA-2008-DamaseviciusST #component #design #diagrams #generative #metaprogramming #ontology #using: Domain Ontology-Based Generative Component Design Using Feature Diagrams and Meta-programming Techniques (RD, VS, JT), pp. 338–341.
WCRE-2008-Ebraert #programming: First-Class Change Objects for Feature-Oriented Programming (PE), pp. 319–322.
ICEIS-AIDSS-2008-AccianiFMM #classification #search-based #statistics: Genetic Feature Selection and Statistical Classification of Voids in Concrete Structure (GA, GF, DM, DM), pp. 231–234.
CIKM-2008-FeiH #classification #graph: Structure feature selection for graph classification (HF, JH), pp. 991–1000.
CIKM-2008-FormanK #classification #performance: Extremely fast text feature extraction for classification and indexing (GF, EK), pp. 1221–1230.
CIKM-2008-LiuLNBMG #dataset #performance #preprocessor #realtime #scalability: Real-time data pre-processing technique for efficient feature extraction in large scale datasets (YL, LVL, RSN, KB, PM, CLG), pp. 981–990.
ICML-2008-ParrLTPL #analysis #approximate #learning #linear #modelling: An analysis of linear models, linear value-function approximation, and feature selection for reinforcement learning (RP, LL, GT, CPW, MLL), pp. 752–759.
ICML-2008-RaykarKBDR #automation #induction #learning #multi: Bayesian multiple instance learning: automatic feature selection and inductive transfer (VCR, BK, JB, MD, RBR), pp. 808–815.
ICML-2008-WangYQZ #analysis #component #composition: Dirichlet component analysis: feature extraction for compositional data (HYW, QY, HQ, HZ), pp. 1128–1135.
ICPR-2008-ChouaibTTCV #algorithm #classification #search-based: Feature selection combining genetic algorithm and Adaboost classifiers (HC, ORT, ST, FC, NV), pp. 1–4.
ICPR-2008-HidakaK #optimisation #using: Non-Neighboring Rectangular Feature selection using Particle Swarm Optimization (AH, TK), pp. 1–4.
ICPR-2008-KrizekKH #algorithm: Feature condensing algorithm for feature selection (PK, JK, VH), pp. 1–4.
ICPR-2008-LiDM #learning #locality #using: Localized feature selection for Gaussian mixtures using variational learning (YL, MD, YM), pp. 1–4.
ICPR-2008-LiLS #invariant #recognition: Redundant DWT based translation invariant wavelet feature extraction for face recognition (DL, HL, ZS), pp. 1–4.
ICPR-2008-SpringerK: Feature selection via decision tree surrogate splits (CS, WPK), pp. 1–5.
ICPR-2008-TsuchiyaF #using: A method of feature selection using contribution ratio based on boosting (MT, HF), pp. 1–4.
ICPR-2008-WangY #image #realtime: Feature selection for real-time image matching systems (QW, SY), pp. 1–4.
ICPR-2008-XuZW #detection #semantics: Semantic feature extraction for accurate eye corner detection (CX, YZ, ZW), pp. 1–4.
ICPR-2008-YangB08a #recognition #sketching: Feature extraction method based on cascade noise elimination for sketch recognition (JY, HB), pp. 1–4.
ICPR-2008-YangWRY: Feature Extraction base on Local Maximum Margin Criterion (WY, JW, MR, JY), pp. 1–4.
KDD-2008-BoutsidisMD #analysis #component: Unsupervised feature selection for principal components analysis (CB, MWM, PD), pp. 61–69.
KDD-2008-ChenW #classification #metric #named #performance #problem: FAST: a roc-based feature selection metric for small samples and imbalanced data classification problems (XwC, MW), pp. 124–132.
KDD-2008-YuDL: Stable feature selection via dense feature groups (LY, CHQD, SL), pp. 803–811.
SEKE-2008-FernandesWM #modelling #product line: Feature Modeling for Context-Aware Software Product Lines (PF, CW, LGPM), pp. 758–763.
SIGIR-2008-PengMO #automation #documentation #retrieval #web: Automatic document prior feature selection for web retrieval (JP, CM, IO), pp. 761–762.
SPLC-2008-CzarneckiSW #modelling: Sample Spaces and Feature Models: There and Back Again (KC, SS, AW), pp. 22–31.
SPLC-2008-HartmannT #diagrams #multi #product line #using #variability: Using Feature Diagrams with Context Variability to Model Multiple Product Lines for Software Supply Chains (HH, TT), pp. 12–21.
SPLC-2008-WhiteSBTC #automation #fault #modelling #product line: Automated Diagnosis of Product-Line Configuration Errors in Feature Models (JW, DCS, DB, PT, ARC), pp. 225–234.
REFSQ-2008-WebersTS #approach #modelling #requirements: Connecting Feature Models and AUTOSAR: An Approach Supporting Requirements Engineering in Automotive Industries (WW, CT, KS), pp. 95–108.
ASE-2008-Dominguez #detection #interactive: Feature Interaction Detection in the Automotive Domain (ALJD), pp. 521–524.
ASE-2008-GeW #framework #generative #modelling #named #platform: Rhizome: A Feature Modeling and Generation Platform (GG, EJWJ), pp. 375–378.
SAC-2008-BragaOM #estimation #optimisation #parametricity: A GA-based feature selection and parameters optimization for support vector regression applied to software effort estimation (PLB, ALIO, SRLM), pp. 1788–1792.
SAC-2008-MengleG #algorithm #ambiguity #classification #using: Using ambiguity measure feature selection algorithm for support vector machine classifier (SSRM, NG), pp. 916–920.
SAC-2008-RibeiroTT #algorithm: A new algorithm for data discretization and feature selection (MXR, AJMT, CTJ), pp. 953–954.
SAC-2008-TakanoC #documentation #feedback: A light-weight feedback method for reconstructing a document vector space on a feature extraction model (KT, XC), pp. 1169–1170.
SAC-2008-ZhangMD #fuzzy #image #retrieval #set #using: Texture feature extraction and description using fuzzy set of main dominant directions of variable scales in content-based medical image retrieval (GZ, ZMM, LD), pp. 1760–1761.
ATEM-J-2006-HeymansSTBMC #diagrams: Evaluating formal properties of feature diagram languages (PH, PYS, JCT, YB, RM, AC), pp. 281–302.
GPCE-2008-ApelKL #calculus #java #programming #refinement: Feature featherweight java: a calculus for feature-oriented programming and stepwise refinement (SA, CK, CL), pp. 101–112.
GPCE-2008-KimKB #composition #interactive #on the: On the modularity of feature interactions (CHPK, CK, DSB), pp. 23–34.
GPCE-2008-MendoncaWCC #compilation #modelling #performance #scalability: Efficient compilation techniques for large scale feature models (MM, AW, KC, DDC), pp. 13–22.
DRR-2007-JoutelEBE #classification: Curvelets based feature extraction of handwritten shapes for ancient manuscripts classification (GJ, VE, SB, HE).
ICDAR-2007-AbedM #comparison #preprocessor #recognition: Comparison of Different Preprocessing and Feature Extraction Methods for Offline Recognition of Handwritten ArabicWords (HEA, VM), pp. 974–978.
ICDAR-2007-VamvakasGPS #performance #recognition #reduction: An Efficient Feature Extraction and Dimensionality Reduction Scheme for Isolated Greek Handwritten Character Recognition (GV, BG, SP, NS), pp. 1073–1077.
ICDAR-2007-ZiaratbanFF #recognition #using: Language-Based Feature Extraction Using Template-Matching In Farsi/Arabic Handwritten Numeral Recognition (MZ, KF, FF), pp. 297–301.
CSMR-2007-PengWZ #adaptation #component #evolution: A Feature-Oriented Adaptive Component Model for Dynamic Evolution (XP, YW, WZ), pp. 49–57.
ICSM-2007-WalkinshawRW #using: Feature Location and Extraction using Landmarks and Barriers (NW, MR, MW), pp. 54–63.
CIG-2007-YannakakisH #game studies: Game and Player Feature Selection for Entertainment Capture (GNY, JH), pp. 244–251.
HCI-AS-2007-JiangSZF #design #interactive: An Interactive Evolutionary Design System with Feature Extraction (XJ, SS, TZ, SF), pp. 1085–1094.
CIKM-2007-HouleG: A correlation-based model for unsupervised feature selection (MEH, NG), pp. 897–900.
CIKM-2007-Metzler #automation #information retrieval #markov #random: Automatic feature selection in the markov random field model for information retrieval (DM), pp. 253–262.
ICML-2007-CaoSSYC #kernel: Feature selection in a kernel space (BC, DS, JTS, QY, ZC), pp. 121–128.
ICML-2007-ChenJ #classification #set: Minimum reference set based feature selection for small sample classifications (XwC, JCJ), pp. 153–160.
ICML-2007-SongSGBB #dependence #estimation: Supervised feature selection via dependence estimation (LS, AJS, AG, KMB, JB), pp. 823–830.
ICML-2007-ZhaoL #learning: Spectral feature selection for supervised and unsupervised learning (ZZ, HL), pp. 1151–1157.
KDD-2007-DasguptaDHJM #classification: Feature selection methods for text classification (AD, PD, BH, VJ, MWM), pp. 230–239.
MLDM-2007-CaoH: Affine Feature Extraction: A Generalization of the Fukunaga-Koontz Transformation (WC, RMH), pp. 160–173.
MLDM-2007-ChengCJY: Nonlinear Feature Selection by Relevance Feature Vector Machine (HC, HC, GJ, KY), pp. 144–159.
SIGIR-2007-GengLQL #ranking: Feature selection for ranking (XG, TYL, TQ, HL), pp. 407–414.
MoDELS-2007-JayaramanWEG #analysis #composition #detection #interactive #product line #using: Model Composition in Product Lines and Feature Interaction Detection Using Critical Pair Analysis (PKJ, JW, AME, HG), pp. 151–165.
SPLC-2007-BragancaM #automation #case study #diagrams #modelling #product line: Automating Mappings between Use Case Diagrams and Feature Models for Software Product Lines (AB, RJM), pp. 3–12.
SPLC-2007-CzarneckiW #diagrams #logic: Feature Diagrams and Logics: There and Back Again (KC, AW), pp. 23–34.
SPLC-2007-JanotaK #higher-order #logic #modelling #reasoning: Reasoning about Feature Models in Higher-Order Logic (MJ, JRK), pp. 13–22.
MoDELS-2007-JayaramanWEG #analysis #composition #detection #interactive #product line #using: Model Composition in Product Lines and Feature Interaction Detection Using Critical Pair Analysis (PKJ, JW, AME, HG), pp. 151–165.
TOOLS-EUROPE-2007-HundtMPS #product line: Improving Alignment of Crosscutting Features with Code in Product Line Engineering (CH, KM, CP, DS), pp. 417–436.
REFSQ-2007-Poppleton #development #specification #towards: Towards Feature-Oriented Specification and Development with Event-B (MP), pp. 367–381.
ASE-2007-Gawley #automation #identification #modelling #variability: Automating the identification of variability realisation techniques from feature models (RG), pp. 555–558.
ASE-2007-LiuMPR #execution #information retrieval: Feature location via information retrieval based filtering of a single scenario execution trace (DL, AM, DP, VR), pp. 234–243.
ASE-2007-ShiriHR #analysis #interactive #maintenance #perspective: Feature interaction analysis: a maintenance perspective (MS, JH, JR), pp. 437–440.
GTTSE-2007-SeguraBCT #automation #graph transformation #modelling #using: Automated Merging of Feature Models Using Graph Transformations (SS, DB, ARC, PT), pp. 489–505.
ICSE-2007-KojarskiL #aspect-oriented #framework #identification #interactive #multi: Identifying Feature Interactions in Multi-Language Aspect-Oriented Frameworks (SK, DHL), pp. 147–157.
SAC-2007-QiT #array #ontology: Integrating gene ontology into discriminative powers of genes for feature selection in microarray data (JQ, JT), pp. 430–434.
SAC-2007-UbayashiN #modelling: Context-aware feature-oriented modeling with an aspect extension of VDM (NU, SN), pp. 1269–1274.
CASE-2007-00010DAR #behaviour #realtime: A Micropositioning System with Real-Time Feature Extraction Capability for Quantifying C. elegans Locomotive Behavior (WW, YS, SJD, MA, PJR), pp. 243–248.
CASE-2007-GarciaV #automation #configuration management #visual notation: Automated Feature Selection Methodology for Reconfigurable Automated Visual Inspection Systems (HCG, JRV), pp. 542–547.
CASE-2007-YangM #approach #automation #interactive #matrix #verification: Automatic Feasibility Verification of Object Configurations: A New Approach Based on Feature Interaction Matrices (FY, MMM), pp. 686–691.
CASE-2007-ZhangBGL #hybrid #monitoring: A Hybrid Model with a Weighted Voting Scheme for Feature Selection in Machinery Condition Monitoring (KZ, ADB, FG, YL), pp. 424–429.
DocEng-2006-Ruiz-RicoGR #automation #named #ranking: NEWPAR: an automatic feature selection and weighting schema for category ranking (FRR, JLVG, MCRS), pp. 128–137.
DRR-2006-WangZXWG #image #recognition #robust: Robust feature extraction for character recognition based on binary images (LW, LZ, YX, ZW, HG).
SOFTVIS-2006-BohnetD #graph #visual notation: Visual exploration of function call graphs for feature location in complex software systems (JB, JD), pp. 95–104.
CIKM-2006-LuPLA #identification #machine learning #query: Coupling feature selection and machine learning methods for navigational query identification (YL, FP, XL, NA), pp. 682–689.
ICPR-v1-2006-ChowdhuryGWM #detection: Note on Feature Selection for Polyp Detection in CT Colonography (TAC, OG, PFW, AAM), pp. 1017–1021.
ICPR-v1-2006-FuCLR #classification #image: Boosted Band Ratio Feature Selection for Hyperspectral Image Classification (ZF, TC, NL, ARK), pp. 1059–1062.
ICPR-v1-2006-LangsPDRB #modelling: Active Feature Models (GL, PP, RD, MR, HB), pp. 417–420.
ICPR-v1-2006-MoritaniHS #realtime: Real-Time Object Tracking without Feature Extraction (TM, SH, KS), pp. 747–750.
ICPR-v1-2006-NieseAM #estimation: A Stereo and Color-based Method for Face Pose Estimation and Facial Feature Extraction (RN, AAH, BM), pp. 299–302.
ICPR-v1-2006-WuNC #locality: Biologically Inspired Hierarchical Model for Feature Extraction and Localization (LW, PN, LNC), pp. 259–262.
ICPR-v1-2006-YangZJY #analysis: Unsupervised Discriminant Projection Analysis for Feature Extraction (JY, DZ, ZJ, JYY), pp. 904–907.
ICPR-v2-2006-ChoiLY #classification #using: Feature Extraction for Bank Note Classification Using Wavelet Transform (EC, JL, JY), pp. 934–937.
ICPR-v2-2006-HuangCX: A Wrapper for Feature Selection Based on Mutual Information (JH, YC, XX), pp. 618–621.
ICPR-v2-2006-InoueNK #analysis #kernel #recognition #string #using: Historical Hand-Written String Recognition by Non-linear Discriminant Analysis using Kernel Feature Selection (RI, HN, NK), pp. 1094–1097.
ICPR-v2-2006-KrizekKH #set: Feature selection based on the training set manipulation (PK, JK, VH), pp. 658–661.
ICPR-v2-2006-LiangZ #linear: Feature selection for linear support vector machines (ZL, TZ), pp. 606–609.
ICPR-v2-2006-LiLW #hybrid #ranking: A Hybrid Method of Unsupervised Feature Selection Based on Ranking (YL, BLL, ZFW), pp. 687–690.
ICPR-v2-2006-Liu #classification #polynomial #recognition #using: High Accuracy Handwritten Chinese Character Recognition Using Quadratic Classifiers with Discriminative Feature Extraction (CLL), pp. 942–945.
ICPR-v2-2006-LiuSXR #complexity #image: Image Complexity and Feature Extraction for Steganalysis of LSB Matching Steganography (QL, AHS, JX, BR), pp. 267–270.
ICPR-v2-2006-RinnhoferBJS #alloy: Feature Extraction from Micrographs of Forged Nickel Based Alloy (AR, WB, GJ, MS), pp. 391–394.
ICPR-v2-2006-SomolP #algorithm #keyword #multi #prototype #using: Multi-Subset Selection for Keyword Extraction and Other Prototype Search Tasks Using Feature Selection Algorithms (PS, PP), pp. 736–739.
ICPR-v2-2006-YaslanC #classification #music #using: Audio Music Genre Classification Using Different Classifiers and Feature Selection Methods (YY, ZÇ), pp. 573–576.
ICPR-v3-2006-LiGYCG: Facial Feature Selection Based on SVMs by Regularized Risk Minimization (WL, WG, LY, WC, XG), pp. 540–543.
ICPR-v3-2006-LiuW #algorithm #analysis #component #recognition #search-based: Feature Extraction with Genetic Algorithms Based Nonlinear Principal Component Analysis for Face Recognition (NL, HW), pp. 461–464.
ICPR-v3-2006-PranckevicieneHS: Class Separability in Spaces Reduced By Feature Selection (EP, TH, RLS), pp. 254–257.
ICPR-v3-2006-QinSL #analysis #performance: Efficient Feature Extraction Based on Regularized Uncorrelated Chernoff Discriminant Analysis (AKQ, PNS, ML), pp. 125–128.
ICPR-v3-2006-SagheerTTAM #approach #multi #performance #problem: Fast Feature Extraction Approach for Multi-Dimension Feature Space Problems (AES, NT, RiT, DA, SM), pp. 417–420.
ICPR-v3-2006-XuanZCZSF #distance: Feature Selection based on the Bhattacharyya Distance (GX, XZ, PC, ZZ, YQS, DF), pp. 1232–1235.
ICPR-v3-2006-ZhengYYWY #agile #recognition: A Complete and Rapid Feature Extraction Method for Face Recognition (YJZ, JYY, JY, XW, DY), pp. 469–472.
ICPR-v4-2006-SunY #3d #evaluation #identification: Evaluation of 3D Facial Feature Selection for Individual Facial Model Identification (YS, LY), pp. 562–565.
ICPR-v4-2006-XuanZCZSF06a #distance: Feature Selection based on the Bhattacharyya Distance (GX, XZ, PC, ZZ, YQS, DF), p. 957.
ICPR-v4-2006-ZhangMH #multi #network: Multiscale Feature Extraction of Finger-Vein Patterns Based on Curvelets and Local Interconnection Structure Neural Network (ZZ, SM, XH), pp. 145–148.
KDD-2006-CarvalhoC #learning #online #performance: Single-pass online learning: performance, voting schemes and online feature selection (VRC, WWC), pp. 548–553.
KDD-2006-TsangKK #kernel #performance #set: Efficient kernel feature extraction for massive data sets (IWT, AK, JTK), pp. 724–729.
SPLC-2006-AsikainenMS #concept #modelling: A Unified Conceptual Foundation for Feature Modelling (TA, TM, TS), pp. 31–40.
SPLC-2006-BrownGBSKG #behaviour #embedded #modelling #product line #weaving: Weaving Behavior into Feature Models for Embedded System Families (TJB, RG, RB, ITAS, PK, CG), pp. 52–64.
SPLC-2006-CzarneckiKK #modelling #ontology: Feature Models are Views on Ontologies (KC, CHPK, KTK), pp. 41–51.
SPLC-2006-LeeK #approach #configuration management #product line: A Feature-Oriented Approach to Developing Dynamically Reconfigurable Products in Product Line Engineering (JL, KCK), pp. 131–140.
SPLC-2006-LeeKKP #analysis #aspect-oriented #development #product line #programming: Combining Feature-Oriented Analysis and Aspect-Oriented Programming for Product Line Asset Development (KL, KCK, MK, SP), pp. 103–112.
SPLC-2006-SpinczykP #modelling #using: Using Feature Models for Product Derivation (OS, HP), p. 225.
RE-2006-SchobbensHT #diagrams #overview #semantics: Feature Diagrams: A Survey and a Formal Semantics (PYS, PH, JCT), pp. 136–145.
SAC-2006-CombarroMRD #categorisation #metric: Angular measures for feature selection in text categorization (EFC, EM, JR, ID), pp. 826–830.
SAC-2006-MontanesCRD #categorisation #linear #metric: Finding optimal linear measures for feature selection in text categorization (EM, EFC, JR, ID), pp. 861–862.
SAC-2006-PechenizkiyPT #learning #reduction: The impact of sample reduction on PCA-based feature extraction for supervised learning (MP, SP, AT), pp. 553–558.
DRR-2005-ChenD #verification: Sequence-matching-based feature extraction with applications to signature verification (YC, XD), pp. 76–83.
ICDAR-2005-FinkP #independence #on the #recognition: On Appearance-Based Feature Extraction Methods for Writer-Independent Handwritten Text Recognition (GAF, TP), pp. 1070–1074.
ICDAR-2005-LiuKF #comparison #recognition: Gabor Feature Extraction for Character Recognition: Comparison with Gradient Feature (CLL, MK, HF), pp. 121–125.
ICDAR-2005-LiuMK #classification #recognition #scalability #set #using: Building Compact Classifier for Large Character Set Recognition Using Discriminative Feature Extraction (CLL, RM, MK), pp. 846–850.
ICDAR-2005-RadtkeSW #classification: Intelligent Feature Extraction for Ensemble of Classifiers (PVWR, RS, TW), pp. 866–870.
ICDAR-2005-RichiardiKD #online #verification: Local and Global Feature Selection for On-line Signature Verification (JR, HK, AD), pp. 625–629.
ICDAR-2005-SchlapbachKB #identification: ImprovingWriter Identification by Means of Feature Selection and Extraction (AS, VK, HB), pp. 131–135.
ICDAR-2005-ZhangBS #hybrid #recognition: Hybrid Feature Extraction and Feature Selection for Improving Recognition Accuracy of Handwritten Numerals (PZ, TDB, CYS), pp. 136–140.
VISSOFT-2005-GreevyLW #3d #interactive #visualisation: Visualizing Feature Interaction in 3-D (OG, ML, CW), pp. 114–119.
CAiSE-2005-BenavidesTC #automation #modelling #reasoning: Automated Reasoning on Feature Models (DB, PTMA, ARC), pp. 491–503.
ECIR-2005-ChenDWLZ: AP-Based Borda Voting Method for Feature Extraction in TRECVID-2004 (LC, DD, DW, FL, BZ), pp. 568–570.
ICML-2005-GlocerET #classification #online: Online feature selection for pixel classification (KAG, DE, JT), pp. 249–256.
ICML-2005-Keerthi #classification #effectiveness: Generalized LARS as an effective feature selection tool for text classification with SVMs (SSK), pp. 417–424.
KDD-2005-ZhouFSU #streaming #using: Streaming feature selection using alpha-investing (JZ, DPF, RAS, LHU), pp. 384–393.
MLDM-2005-Bobrowski #modelling: Ranked Modelling with Feature Selection Based on the CPL Criterion Functions (LB), pp. 218–227.
MLDM-2005-HanCY #analysis #component #image #independence #using: Aquaculture Feature Extraction from Satellite Image Using Independent Component Analysis (JGH, KHC, YKY), pp. 660–666.
MLDM-2005-KurganH #approach #predict #sequence: Prediction of Secondary Protein Structure Content from Primary Sequence Alone — A Feature Selection Based Approach (LAK, LH), pp. 334–345.
MLDM-2005-LegrandN #using: Feature Selection Method Using Preferences Aggregation (GL, NN), pp. 203–217.
SEKE-2005-BenavidesTC #constraints #modelling #programming #using: Using Constraint Programming to Reason on Feature Models (DB, PT, ARC), pp. 677–682.
SEKE-2005-LiCLY #analysis #design #evolution #legacy #using: Using Feature-Oriented Analysis to Recover Legacy Software Design for Software Evolution (SL, FC, ZL, HY), pp. 336–341.
SIGIR-2005-YanLZYCCFM #categorisation #named #orthogonal: OCFS: optimal orthogonal centroid feature selection for text categorization (JY, NL, BZ, SY, ZC, QC, WF, WYM), pp. 122–129.
ECMDA-FA-2005-HwanKC #modelling: Synchronizing Cardinality-Based Feature Models and Their Specializations (CHPK, KC), pp. 331–348.
MoDELS-2005-ZhangMZY #approach #component: Transformation from CIM to PIM: A Feature-Oriented Component-Based Approach (WZ, HM, HZ, JY), pp. 248–263.
SPLC-2005-Batory #modelling: Feature Models, Grammars, and Propositional Formulas (DSB), pp. 7–20.
SPLC-2005-KangKLK #case study #legacy #product line #re-engineering: Feature-Oriented Re-engineering of Legacy Systems into Product Line Assets — a Case Study (KCK, MK, JL, BK), pp. 45–56.
SPLC-2005-MassenL #modelling: Determining the Variation Degree of Feature Models (TvdM, HL), pp. 82–88.
MoDELS-2005-ZhangMZY #approach #component: Transformation from CIM to PIM: A Feature-Oriented Component-Based Approach (WZ, HM, HZ, JY), pp. 248–263.
RE-2005-ChenZZM #approach #clustering #modelling #requirements: An Approach to Constructing Feature Models Based on Requirements Clustering (KC, WZ, HZ, HM), pp. 31–40.
RE-2005-ZhangMZ #approach #dependence #modelling #requirements: A Feature-Oriented Approach to Modeling Requirements Dependencies (WZ, HM, HZ), pp. 273–284.
ASE-2005-KoschkeQ #on the: On dynamic feature location (RK, JQ), pp. 86–95.
GTTSE-2005-BenavidesSMC #analysis #automation #csp #java #modelling #using: Using Java CSP Solvers in the Automated Analyses of Feature Models (DB, SS, PTMA, ARC), pp. 399–408.
GPCE-2005-ApelLRS #aspect-oriented #programming: FeatureC++: On the Symbiosis of Feature-Oriented and Aspect-Oriented Programming (SA, TL, MR, GS), pp. 125–140.
CSMR-2004-PashovRP #architecture #modelling: Supporting Architectural Restructuring by Analyzing Feature Models (IP, MR, IP), pp. 25–36.
ICSM-2004-ZhaoZHMS #algorithm #scalability: Alternative Scalable Algorithms for Lattice-Based Feature Location (WZ, LZ, DH, HM, JS), p. 528.
CIKM-2004-WangL #categorisation: Feature selection with conditional mutual information maximin in text categorization (GW, FHL), pp. 342–349.
ICML-2004-Forman #classification #multi: A pitfall and solution in multi-class feature selection for text classification (GF).
ICML-2004-GabrilovichM #categorisation #using: Text categorization with many redundant features: using aggressive feature selection to make SVMs competitive with C4.5 (EG, SM).
ICML-2004-Gilad-BachrachNT #algorithm: Margin based feature selection — theory and algorithms (RGB, AN, NT).
ICML-2004-HardinTA #linear: A theoretical characterization of linear SVM-based feature selection (DPH, IT, CFA).
ICML-2004-KimK: Gradient LASSO for feature selection (YK, JK).
ICML-2004-YeJLP #analysis #linear: Feature extraction via generalized uncorrelated linear discriminant analysis (JY, RJ, QL, HP).
ICPR-v1-2004-BariamisIMK #architecture #image #realtime: An FPGA-Based Architecture for Real Time Image Feature Extraction (DGB, DKI, DEM, SAK), pp. 801–804.
ICPR-v1-2004-GunterB #evaluation #recognition #word: An Evaluation of Ensemble Methods in Handwritten Word Recognition Based on Feature Selection (SG, HB), pp. 388–392.
ICPR-v1-2004-LiHS #image #programming #retrieval #search-based #semantics #using: Semantic Feature Extraction Using Genetic Programming in Image Retrieval (QL, HH, ZS), pp. 648–651.
ICPR-v1-2004-Rivero-MorenoB: Texture Feature Extraction and Indexing by Hermite Filters (CJRM, SB), pp. 684–687.
ICPR-v2-2004-ChenLF #adaptation #probability: Probabilistic Tracking with Adaptive Feature Selection (HTC, TLL, CSF), pp. 736–739.
ICPR-v2-2004-FarmerBJ #random #scalability #using: Large Scale Feature Selection Using Modified Random Mutation Hill Climbing (MEF, SB, AKJ), pp. 287–290.
ICPR-v2-2004-MitraM #clustering: Feature Selection and Gene Clustering from Gene Expression Data (PM, DDM), pp. 343–346.
ICPR-v2-2004-Nagao #approach #kernel: Bayesian Approach with Nonlinear Kernels to Feature Extraction (KN), pp. 153–156.
ICPR-v2-2004-PlotzF #analysis #biology #sequence: Feature Extraction for Improved Profile HMM based Biological Sequence Analysis (TP, GAF), pp. 315–318.
ICPR-v2-2004-StefanoGM #approach #multi #online #segmentation: A Multiresolution Approach to On-line Handwriting Segmentation and Feature Extraction (CDS, MG, AM), pp. 614–617.
ICPR-v2-2004-TahirBKA #classification #using: Feature Selection using Tabu Search for Improving the Classification Rate of Prostate Needle Biopsies (MAT, AB, FK, AA), pp. 335–338.
ICPR-v2-2004-XuanDKHCW #multi #predict #profiling #robust: Robust Feature Selection by Weighted Fisher Criterion for Multiclass Prediction in Gene Expression Profiling (JX, YD, JIK, EPH, RC, YJW), pp. 291–294.
ICPR-v3-2004-WuZZ #linear #using: Relevant Linear Feature Extraction Using Side-information and Unlabeled Data (FW, YZ, CZ), pp. 582–585.
ICPR-v4-2004-MarkouS: Feature Selection based on a Black Hole Model of Data Reorganization (MM, SS), pp. 565–568.
ICPR-v4-2004-PaclikVD #algorithm #multi: Multi-Class Extensions of the GLDB Feature Extraction Algorithm for Spectral Data (PP, SV, RPWD), pp. 629–632.
ICPR-v4-2004-Xiao-JunKYMW #algorithm #recognition: A New Direct LDA (D-LDA) Algorithm for Feature Extraction in Face Recognition (XW, JK, JYY, KM, SW), pp. 545–548.
KDD-2004-Cantu-PazNK: Feature selection in scientific applications (ECP, SDN, CK), pp. 788–793.
KDD-2004-YuL #array: Redundancy based feature selection for microarray data (LY, HL), pp. 737–742.
SIGIR-2004-MladenicBGM #classification #interactive #linear #modelling #using: Feature selection using linear classifier weights: interaction with classification models (DM, JB, MG, NMF), pp. 234–241.
SPLC-2004-CzarneckiHE #modelling #staged #using: Staged Configuration Using Feature Models (KC, SH, UWE), pp. 266–283.
UML-2004-DologN #collaboration #diagrams #modelling #uml #using: Using UML-based Feature Models and UML Collaboration Diagrams to Information Modelling for Web-Based Applications (PD, WN), pp. 425–439.
FSE-2004-MeziniO #aspect-oriented #programming #variability: Variability management with feature-oriented programming and aspects (MM, KO), pp. 127–136.
ICSE-2004-Batory #programming: Feature-Oriented Programming and the AHEAD Tool Suite (DSB), pp. 702–703.
ICSE-2004-WohlstadterJD #design #distributed #implementation: Design and Implementation of Distributed Crosscutting Features with DADO (EW, SJ, PTD), pp. 706–707.
ICSE-2004-ZhaoZLSY #approach #named #towards: SNIAFL: Towards a Static Non-Interactive Approach to Feature Location (WZ, LZ, YL, JS, FY), pp. 293–303.
SAC-2004-MotaiK #3d #locality #robust: Concatenate feature extraction for robust 3D elliptic object localization (YM, AK), pp. 21–28.
ICDAR-2003-AblavskyS #automation #documentation #identification: Automatic Feature Selection with Applications to Script Identification of Degraded Documents (VA, MRS), pp. 750–754.
ICDAR-2003-BlumensteinVB #novel #recognition: A Novel Feature Extraction Technique for the Recognition of Segmented Handwritten Characters (MB, BV, HB), pp. 137–141.
ICDAR-2003-GocciaBSD #classification #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-MenotiBFB #approach #segmentation: Segmentation of Postal Envelopes for Address Block Location: an approach based on feature selection in wavelet space (DM, DLB, JF, AdSBJ), pp. 699–703.
ICDAR-2003-Mori #recognition #using #video: Video text recognition using feature compensation as category-dependent feature extraction (MM), pp. 645–649.
ICDAR-2003-MoritaSBS03a #algorithm #multi #recognition #search-based #using #word: Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition (MEM, RS, FB, CYS), pp. 666–670.
ICDAR-2003-OliveiraSBS #algorithm #approach #multi #search-based: Feature Selection for Ensembles: A Hierarchical Multi-Objective Genetic Algorithm Approach (LESdO, RS, FB, CYS), p. 676–?.
ICDAR-2003-WuM #recognition: Feature Extraction by Hierarchical Overlapped Elastic Meshing for Handwritten Chinese Character Recognition (TW, SM), pp. 529–533.
ICML-2003-LiuLCM #clustering #evaluation: An Evaluation on Feature Selection for Text Clustering (TL, SL, ZC, WYM), pp. 488–495.
ICML-2003-PerkinsT #online #using: Online Feature Selection using Grafting (SP, JT), pp. 592–599.
ICML-2003-YuL #performance: Feature Selection for High-Dimensional Data: A Fast Correlation-Based Filter Solution (LY, HL), pp. 856–863.
KDD-2003-PampalkGW #visualisation: Visualizing changes in the structure of data for exploratory feature selection (EP, WG, GW), pp. 157–166.
ICSE-2003-WohlstadterJD #distributed #middleware #named: DADO: Enhancing Middleware to Support Crosscutting Features in Distributed, Heterogeneous Systems (EW, SJ, PTD), pp. 174–186.
SAC-2003-ChenYT: The Bitmap-based Feature Selection Method (WCC, MCY, SST), pp. 465–469.
SAC-2003-Tufts-ConradZZ #named #summary: SOM — Feature Extraction from Patient Discharge Summaries (DJTC, ANZH, DZ), pp. 263–267.
CBSE-2003-JiaA #interactive #runtime: Run-Time Management of Feature Interactions (YJ, JMA), p. 7.
DocEng-2002-WibowoW #categorisation: Simple and accurate feature selection for hierarchical categorisation (WW, HEW), pp. 111–118.
CAiSE-2002-BerlinM #database #machine learning #using: Database Schema Matching Using Machine Learning with Feature Selection (JB, AM), pp. 452–466.
CIKM-2002-RogatiY #classification: High-performing feature selection for text classification (MR, YY), pp. 659–661.
ICML-2002-JensenN #bias #learning #relational: Linkage and Autocorrelation Cause Feature Selection Bias in Relational Learning (DJ, JN), pp. 259–266.
ICML-2002-LiuMY: Feature Selection with Selective Sampling (HL, HM, LY), pp. 395–402.
ICML-2002-SlonimBFT #markov #memory management #multi: Discriminative Feature Selection via Multiclass Variable Memory Markov Model (NS, GB, SF, NT), pp. 578–585.
ICML-2002-TeowLNY #approach #fault: Refining the Wrapper Approach — Smoothed Error Estimates for Feature Selection (LNT, HL, HTN, EY), pp. 626–633.
ICPR-v1-2002-DockstaderBT #analysis: Feature Extraction for the Analysis of Gait and Human Motion (SLD, KAB, AMT), pp. 5–8.
ICPR-v1-2002-OliveiraSBS #algorithm #multi #recognition #search-based #using: Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Digit Recognition (LESdO, RS, FB, CYS), pp. 568–571.
ICPR-v1-2002-SinghSM #clustering #recognition: Feature Selection for Face Recognition Based on Data Partitioning (SS, MS, MM), pp. 680–683.
ICPR-v2-2002-GuptaDD #automation #classification #fault: Beam Search for Feature Selection in Automatic SVM Defect Classification (PG, DSD, DD), pp. 212–215.
ICPR-v2-2002-MurpheyL #classification #multi #network: Feature Extraction for a Multiple Pattern Classification Neural Network System (YLM, YL), pp. 220–223.
ICPR-v2-2002-OhLM #algorithm #search-based: Local Search-Embedded Genetic Algorithms for Feature Selection (ISO, JSL, BRM), pp. 148–151.
ICPR-v2-2002-Perez-JimenezP: Radial Projections for Non-Linear Feature Extraction (AJPJ, JCPC), pp. 444–447.
ICPR-v2-2002-Torkkola02a #learning #problem: Learning Feature Transforms Is an Easier Problem Than Feature Selection (KT), pp. 104–107.
ICPR-v2-2002-ZhangBS #2d #recognition #using: Recognition of Similar Objects Using 2-D Wavelet-Fractal Feature Extraction (PZ, TDB, CYS), pp. 316–319.
ICPR-v3-2002-Cuesta-FrauPAN #case study #clustering #comparative: Feature Extraction Methods Applied to the Clustering of Electrocardiographic Signals. A Comparative Study (DCF, JCPC, GAG, DN), pp. 961–964.
ICPR-v3-2002-GarciaP #integration #multi #pattern matching #pattern recognition #recognition: Improving Texture Pattern Recognition by Integration of Multiple Texture Feature Extraction Methods (MAG, DP), pp. 7–10.
ICPR-v3-2002-HontaniSKA #image #symmetry: Vibratory Image Feature Extraction Based on Local Log-Polar Symmetry (HH, JS, AK, SA), pp. 839–842.
ICPR-v3-2002-MoriSH #recognition: Category-Dependent Feature Extraction for Recognition of Degraded Handwritten Characters (MM, MS, NH), pp. 155–159.
ICPR-v4-2002-Al-AniD: Feature Selection sing a Mutual Information Based Measure (AAA, MD), pp. 82–85.
ICPR-v4-2002-GokberkAA #invariant #recognition: Feature Selection for Pose Invariant Face Recognition (BG, LA, EA), pp. 306–309.
ICPR-v4-2002-WangDL #recognition: Optimized Gabor Filter Based Feature Extraction for Character Recognition (XW, XD, CL), pp. 223–226.
ICPR-v4-2002-XiL #detection #using: Face Detection and Facial Feature Extraction Using Support Vector Machines (DX, SWL), pp. 209–212.
ICPR-v4-2002-ZhuS #adaptation #analysis #detection #statistics: Discriminant Analysis and Adaptive Wavelet Feature Selection for Statistical Object Detection (YZ, SCS), pp. 86–89.
SPLC-2002-FerberHS #dependence #interactive #legacy #modelling #product line #re-engineering: Feature Interaction and Dependencies: Modeling Features for Reengineering a Legacy Product Line (SF, JH, JS), pp. 235–256.
SPLC-2002-FeyFB #metamodelling #modelling #usability: Feature Modeling: A Meta-Model to Enhance Usability and Usefulness (DF, RF, AB), pp. 198–216.
ICDAR-2001-GaoJYH #approach #recognition: A New Stroke-Based Directional Feature Extraction Approach for Handwritten Chinese Character Recognition (XG, LJ, JY, JH), pp. 635–639.
ICDAR-2001-GomesL #fuzzy #recognition #set: Feature Extraction Based on Fuzzy Set Theory for Handwriting Recognition (NRG, LLL), pp. 655–659.
ICDAR-2001-HusseinWK #algorithm #overview #search-based: Genetic Algorithms for Feature Selection and Weighting, A Review and Study (FH, RKW, NNK), p. 1240–?.
ICDAR-2001-MoriSHMM #recognition #robust: Robust Feature Extraction Based on Run-Length Compensation for Degraded Handwritten Character Recognition (MM, MS, NH, HM, NM), pp. 650–654.
ICDAR-2001-NishimuraTMMN #recognition #using: Off-line Hand-written Character Recognition Using Integrated 1D HMMs Based on Feature Extraction Filters (HN, MT, MM, HM, YN), pp. 417–423.
ICDAR-2001-RheeCK #online #segmentation #using #verification: On-Line Signature Verification Using Model-Guided Segmentation and Discriminative Feature Selection for Skilled Forgeries (THR, SJC, JHK), pp. 645–649.
ICDAR-2001-SuralD #algorithm #search-based: A Genetic Algorithm for Feature Selection in a Neuro-Fuzzy OCR System (SS, PKD), pp. 987–991.
ICDAR-2001-XueG #graph #image: Building Skeletal Graphs for Structural Feature Extraction on Handwriting Images (HX, VG), pp. 96–100.
JCDL-2001-LiuW #automation #classification: Feature selection for automatic classification of musical instrument sounds (ML, CW), pp. 247–248.
CSMR-2001-WildeBPR #case study #fortran #legacy: A Case Study of Feature Location in Unstructured Legacy Fortran Code (NW, MB, HP, VR), pp. 68–76.
CIKM-2001-KolczPK #categorisation #summary: Summarization as Feature Selection for Text Categorization (AK, VP, JKK), pp. 365–370.
CIKM-2001-PollyW #pattern matching #performance #robust: Efficient and Robust Feature Extraction and Pattern Matching of Time Series by a Lattice Structure (WPMP, MHW), pp. 271–278.
ICML-2001-Das #hybrid: Filters, Wrappers and a Boosting-Based Hybrid for Feature Selection (SD), pp. 74–81.
ICML-2001-NgJ #classification #convergence: Convergence rates of the Voting Gibbs classifier, with application to Bayesian feature selection (AYN, MIJ), pp. 377–384.
ICML-2001-XingJK #array: Feature selection for high-dimensional genomic microarray data (EPX, MIJ, RMK), pp. 601–608.
MLDM-2001-KollmarH #learning: Feature Selection for a Real-World Learning Task (DK, DHH), pp. 157–172.
SIGIR-2001-Pickens #music #retrieval: Feature Selection for Polyphonic Music Retrieval (JP), pp. 428–429.
HPDC-2001-KuntrarukP #data mining #distributed #mining #parallel #using: Massively Parallel Distributed Feature Extraction in Textual Data Mining Using HDDI(tm) (JK, WMP), pp. 363–370.
ECDL-2000-GalavottiSS #automation #categorisation #using: Experiments on the Use of Feature Selection and Negative Evidence in Automated Text Categorization (LG, FS, MS), pp. 59–68.
ECDL-2000-MugeGMPRSPMRVA #automation #recognition: Automatic Feature Extraction and Recognition for Digital Access of Books of the Renaissance (FM, IG, MM, PP, VR, NS, JRCP, AM, MR, PV, AMdA), pp. 1–13.
IWPC-2000-ChenR #case study #dependence #graph #using: Case Study of Feature Location Using Dependence Graph (KC, VR), pp. 241–247.
ICML-2000-Hall #machine learning: Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning (MAH), pp. 359–366.
ICML-2000-Talavera #concept #incremental #learning #probability: Feature Selection and Incremental Learning of Probabilistic Concept Hierarchies (LT), pp. 951–958.
ICPR-v2-2000-BaesensVVD #network #optimisation: Wrapped Feature Selection by Means of Guided Neural Network Optimization (BB, SV, JV, GD), pp. 2113–2116.
ICPR-v2-2000-BhanuBT #image #logic: Logical Templates for Feature Extraction in Fingerprint Images (BB, MB, XT), pp. 2846–2850.
ICPR-v2-2000-Caelli #image #learning #modelling #performance #predict: Learning Image Feature Extraction: Modeling, Tracking and Predicting Human Performance (TC), pp. 2215–2218.
ICPR-v2-2000-DuinLH #linear #multi: Multi-Class Linear Feature Extraction by Nonlinear PCA (RPWD, ML, RHU), pp. 2398–2401.
ICPR-v2-2000-GaoD #algorithm #classification #on the: On Improvement of Feature Extraction Algorithms for Discriminative Pattern Classification (JG, XD), pp. 2101–2104.
ICPR-v2-2000-GuoM #approach #automation #hybrid #statistics: Automatic Feature Selection — A Hybrid Statistical Approach (HG, YLM), pp. 2382–2385.
ICPR-v2-2000-HermesB: Feature Selection for Support Vector Machines (LH, JMB), pp. 2712–2715.
ICPR-v2-2000-LeeC #multi #optimisation #problem: Optimizing Feature Extraction for Multiclass Problems (CL, EC), pp. 2402–2405.
ICPR-v2-2000-LingC #bound #performance: Fast and Efficient Feature Extraction Based on Bayesian Decision Boundaries (LLL, HMC), pp. 2390–2393.
ICPR-v2-2000-RitterS: Profile and Feature Extraction from Chromosomes (GR, GS), pp. 2287–2290.
ICPR-v2-2000-Schulerud #analysis #bias #fault #linear: Bias of Error Rates in Linear Discriminant Analysis Caused by Feature Selection and Sample Size (HS), pp. 2372–2377.
ICPR-v2-2000-SomolP #algorithm: Oscillating Search Algorithms for Feature Selection (PS, PP), pp. 2406–2409.
ICPR-v2-2000-ZhangDL #classification #design #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-CostaBG #algorithm: Level Curve Tracking Algorithm for Textural Feature Extraction (JPDC, PB, CG), pp. 3921–3924.
ICPR-v3-2000-Ichimura #segmentation #using: Motion Segmentation Using Feature Selection and Subspace Method Based on Shape Space (NI), pp. 3858–3864.
ICPR-v3-2000-Ichimura00a #3d: Token Grouping Based on 3D Motion and Feature Selection in Object Tracking (NI), pp. 7130–7136.
ICPR-v3-2000-KimCL #detection #performance #using: Fast Scene Change Detection Using Direct Feature Extraction from MPEG Compressed Videos (YMK, SWC, SWL), pp. 3178–3181.
ICPR-v4-2000-KoLB #image #performance #retrieval #using: Region-Based Image Retrieval System Using Efficient Feature Description (BK, HSL, HB), pp. 4283–4286.
KDD-2000-DyB #interactive #visualisation: Visualization and interactive feature selection for unsupervised data (JGD, CEB), pp. 360–364.
KDD-2000-KimSM #learning #search-based: Feature selection in unsupervised learning via evolutionary search (YK, WNS, FM), pp. 365–369.
SPLC-2000-HeinSV #industrial #modelling: Applying feature models in industrial settings (AH, MS, RVM), pp. 47–70.
SAC-2000-BaldwinMP #analysis #semantics: Semantic Discrimination Analysis for Feature Selection (JFB, TPM, CP), pp. 519–523.
ICDAR-1999-KavianifarA #multi #preprocessor: Preprocessing and Structural Feature Extraction for a Multi-Fonts Arabic/Persian OCR (MK, AA), pp. 213–216.
ICDAR-1999-NishimuraKMN #algorithm #multi #recognition #using: Off-line Character Recognition using HMM by Multiple Directional Feature Extraction and Voting with Bagging Algorithm (HN, MK, MM, YN), pp. 49–52.
ICDAR-1999-TangT: Feature Extraction by Fractal Dimensions (YYT, YT), pp. 217–220.
ICDAR-1999-TaoT: The Feature Extraction of Chinese Character based on Contour Information (YT, YYT), pp. 637–640.
ICDAR-1999-VaidyaDGS #approach #documentation #recognition #statistics: Statistical Approach to Feature Extraction for Numeral Recognition from Degraded Documents (VV, VD, DG, BS), pp. 273–276.
FM-v1-1999-Bousquet #case study #detection #experience #interactive #model checking #testing #using: Feature Interaction Detection Using Testing and Model-Checking Experience Report (LdB), pp. 622–641.
ICML-1999-MladenicG #naive bayes: Feature Selection for Unbalanced Class Distribution and Naive Bayes (DM, MG), pp. 258–267.
ICML-1999-Talavera #clustering #preprocessor: Feature Selection as a Preprocessing Step for Hierarchical Clustering (LT), pp. 389–397.
ICML-1998-BradleyM: Feature Selection via Concave Minimization and Support Vector Machines (PSB, OLM), pp. 82–90.
ICML-1998-Ng #learning #on the: On Feature Selection: Learning with Exponentially Many Irrelevant Features as Training Examples (AYN), pp. 404–412.
ICPR-1998-FunadaOMTNMSWY: Feature extraction method for palmprint considering elimination of creases (JiF, NO, MM, TT, KN, AM, TS, TW, YY), pp. 1849–1854.
ICPR-1998-HyvarinenOHH #analysis #component #image #independence: Image feature extraction by sparse coding and independent component analysis (AH, EO, POH, JH), pp. 1268–1273.
ICPR-1998-KimKA: Feature extraction of edge by directional computation of gray-scale variation (KCK, DYK, JKA), pp. 1022–1027.
ICPR-1998-OhtaSN #modelling #recognition #using: Recognition of facial expressions using muscle-based feature models (HO, HS, HN), pp. 1379–1381.
ICPR-1998-OtsukaHSF: Feature extraction of temporal texture based on spatiotemporal motion trajectory (KO, TH, SS, MF), pp. 1047–1051.
ICPR-1998-RohrerGPB #recognition: Feature selection in melanoma recognition (RR, HG, AP, MB), pp. 1668–1670.
ICPR-1998-WarkSC #approach #identification #modelling #statistics: An approach to statistical lip modelling for speaker identification via chromatic feature extraction (TW, SS, VC), pp. 123–125.
KDD-1998-KontkanenMST #classification #named: BAYDA: Software for Bayesian Classification and Feature Selection (PK, PM, TS, HT), pp. 254–258.
ICDAR-1997-ChungY #comparison #performance #recognition: Performance comparison of several feature selection methods based on node pruning in handwritten character recognition (KC, JY), pp. 11–15.
ICDAR-1997-Nishida #bound #documentation #image: Boundary Feature Extraction from Gray-Scale Document Images (HN), pp. 132–141.
ICDAR-1997-Yamada #recognition: Non-uniformly Sampled Feature Extraction Method for Kanji Character Recognition (KY), pp. 200–205.
ACIR-1997-Moulinier #preprocessor: Feature Selection: A Useful Preprocessing Step (IM).
ICML-1997-DevaneyR #clustering #concept #performance: Efficient Feature Selection in Conceptual Clustering (MD, AR), pp. 92–97.
ICML-1997-YangP #case study #categorisation #comparative: A Comparative Study on Feature Selection in Text Categorization (YY, JOP), pp. 412–420.
SIGIR-1997-NgGL #case study #categorisation #learning #usability: Feature Selection, Perceptron Learning, and a Usability Case Study for Text Categorization (HTN, WBG, KLL), pp. 67–73.
ECOOP-1997-Prehofer #fresh look #programming: Feature-Oriented Programming: A Fresh Look at Objects (CP), pp. 419–443.
ICML-1996-KollerS #towards: Toward Optimal Feature Selection (DK, MS), pp. 284–292.
ICML-1996-LiuS #approach #probability: A Probabilistic Approach to Feature Selection — A Filter Solution (HL, RS), pp. 319–327.
ICPR-1996-ChenHW #geometry #image #modelling #recognition #using: Model-based object recognition using range images by combining morphological feature extraction and geometric hashing (CSC, YPH, JLW), pp. 565–569.
ICPR-1996-ChiangG #framework #hybrid #recognition: A hybrid feature extraction framework for handwritten numeric fields recognition (JHC, PDG), pp. 436–440.
ICPR-1996-KimuraWM #on the #problem: On feature extraction for limited class problem (FK, TW, YM), pp. 191–194.
ICPR-1996-LernerGADR #classification #network: Feature extraction by neural network nonlinear mapping for pattern classification (BL, HG, MA, ID, YR), pp. 320–324.
ICPR-1996-Nouza #markov #modelling #recognition #speech: Feature selection methods for hidden Markov model-based speech recognition (JN), pp. 186–190.
ICPR-1996-SaberT #cost analysis #detection #symmetry #using: Face detection and facial feature extraction using color, shape and symmetry-based cost functions (ES, AMT), pp. 654–658.
ICPR-1996-SakaguchiM #recognition: Face feature extraction from spatial frequency for dynamic expression recognition (TS, SM), pp. 451–455.
ICPR-1996-TorkarP #image: Feature extraction from aerial images and structural stereo matching (DT, NP), pp. 880–884.
ICPR-1996-Webb #multi #scalability #using: Nonlinear feature extraction with radial basis functions using a weighted multidimensional scaling stress measure (ARW), pp. 635–639.
ICPR-1996-WindeattT: Analytical feature extraction and spectral summation (TW, RT), pp. 315–319.
ICPR-1996-WuCY96a #verification: Facial feature extraction and face verification (HW, QC, MY), pp. 484–488.
ICPR-1996-XuanCW #distance: Bhattacharyya distance feature selection (GX, PC, MW), pp. 195–199.
ICPR-1996-Yamakawa #learning #recognition: Matchability-oriented feature selection for recognition structure learning (HY), pp. 123–127.
ICPR-1996-ZongkerJ #algorithm #evaluation: Algorithms for feature selection: An evaluation (DEZ, AKJ), pp. 18–22.
KDD-1996-RicheldiL #effectiveness: Performing Effective Feature Selection by Investigating the Deep Structure of the Data (MR, PLL), pp. 379–383.
ISSTA-1996-PomakisA #analysis #interactive #reachability: Reachability Analysis of Feature Interactions: A Progress Report (KPP, JMA), pp. 216–223.
ICDAR-v1-1995-UtschickNKSN #classification #evaluation #network: The evaluation of feature extraction criteria applied to neural network classifiers (WU, PN, CK, AS, JAN), pp. 315–318.
ICDAR-v2-1995-SauvolaP #analysis #classification #performance #segmentation #using: Page segmentation and classification using fast feature extraction and connectivity analysis (JJS, MP), pp. 1127–1131.
KDD-1995-SeshadriSW #data mining #mining: Feature Extraction for Massive Data Mining (VS, RS, SMW), pp. 258–262.
SEKE-1995-Borstler #classification #reuse: Feature-Oriented Classification for Software Reuse (JB), pp. 204–211.
ICML-1994-Skalak #algorithm #prototype #random: Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms (DBS), pp. 293–301.
SIGIR-1994-ConradU #database: A System for Discovering Relationships by Feature Extraction from Text Databases (JGC, MHU), pp. 260–270.
ICDAR-1993-CaesarGM #preprocessor #recognition: Preprocessing and feature extraction for a handwriting recognition system (TC, JMG, EM), pp. 408–411.
ICDAR-1993-HamanakaYT #online #recognition: On-line Japanese character recognition experiments by an off-line method based on normalization-cooperated feature extraction (MH, KY, JT), pp. 204–207.
ICDAR-1993-Nishida #multi #recognition: Structural feature extraction on multiple bases with application to handwritten character recognition systems (HN), pp. 27–30.
ICDAR-1993-SakodaZP #recognition #refinement #testing: Refinement and testing of a character recognition system based on feature extraction in grayscale space (WJS, JZ, TP), pp. 464–469.
ICDAR-1993-TaiLZ #approach #detection #modelling #recognition: A model based detecting approach for feature extraction of off-line handwritten Chinese character recognition (JWT, YJL, LQZ), pp. 826–829.
ML-1992-KiraR #approach: A Practical Approach to Feature Selection (KK, LAR), pp. 249–256.
ML-1992-OliveiraS #induction #using: Constructive Induction Using a Non-Greedy Strategy for Feature Selection (ALO, ALSV), pp. 355–360.
ML-1990-ThintW #clustering #modelling: Feature Extraction and Clustering of Tactile Impressions with Connectionist Models (MT, PPW), pp. 253–258.
ML-1989-Seifert #retrieval #using: A Retrieval Model Using Feature Selection (CMS), pp. 52–54.
DAC-1983-HofmannL #approach #named: HEX: An instruction-driven approach to feature extraction (MH, UL), pp. 331–336.