Stem label$ (all stems)

445 papers:

CASE-2015-ClevelandTDPKDB #automation #programming #recognition #segmentation #semantics

An automated system for semantic object labeling with soft object recognition and dynamic programming segmentation (JC, DT, PD, CJP, TK, KD, JB, VK), pp. 683–690.

DAC-2015-CavigelliMB #embedded #network #realtime

Accelerating real-time embedded scene labeling with convolutional networks (LC, MM, LB), p. 6.

DRR-2015-ClawsonB #automation

Intelligent indexing: a semi-automated, trainable system for field labeling (RC, WAB).

DRR-2015-FuLLQT #diagrams #learning #multi #retrieval

A diagram retrieval method with multi-label learning (SF, XL, LL, JQ, ZT).

SIGMOD-2015-WangLYXZ #approach #network #performance

Efficient Route Planning on Public Transportation Networks: A Labelling Approach (SW, WL, YY, XX, SZ), pp. 967–982.

VLDB-2015-ShinRC #knowledge base #named

Mindtagger: A Demonstration of Data Labeling in Knowledge Base Construction (JS, CR, MJC), pp. 1920–1931.

MSR-2015-MauczkaBSG #commit #dataset #developer

Dataset of Developer-Labeled Commit Messages (AM, FB, CS, TG), pp. 490–493.

SANER-2015-CabotICR #open source

Exploring the use of labels to categorize issues in Open-Source Software projects (JC, JLCI, VC, BR), pp. 550–554.

SANER-2015-IzquierdoCRBC #git #named

GiLA: GitHub label analyzer (JLCI, VC, BR, AB, JC), pp. 479–483.

STOC-2015-AlstrupKTZ #graph

Adjacency Labeling Schemes and Induced-Universal Graphs (SA, HK, MT, UZ), pp. 625–634.

ICALP-v1-2015-KawaseKY #graph

Finding a Path in Group-Labeled Graphs with Two Labels Forbidden (YK, YK, YY), pp. 797–809.

ICALP-v2-2015-DahlgaardKR

A Simple and Optimal Ancestry Labeling Scheme for Trees (SD, MBTK, NR), pp. 564–574.

GaM-2015-Wijs #confluence #detection #lts

Confluence Detection for Transformations of Labelled Transition Systems (AW), pp. 1–15.

CSCW-2015-WeirKGM

Learnersourcing Subgoal Labels for How-to Videos (SAW, JK, KZG, RCM), pp. 405–416.

HIMI-IKD-2015-WhiteFK #generative #interface

Generation of Infotips from Interface Labels (EW, SF, FK), pp. 226–234.

CAiSE-2015-KoschmiderUHO #process

Revising the Vocabulary of Business Process Element Labels (AK, MU, AH, AO), pp. 69–83.

ECIR-2015-EfremovaGC #classification

Classification of Historical Notary Acts with Noisy Labels (JE, AMG, TC), pp. 49–54.

ICML-2015-GasseAE #classification #composition #multi #on the #set

On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property (MG, AA, HE), pp. 2531–2539.

ICML-2015-MenonROW #estimation #learning

Learning from Corrupted Binary Labels via Class-Probability Estimation (AKM, BvR, CSO, BW), pp. 125–134.

ICML-2015-PhamRFA #learning #multi #novel

Multi-instance multi-label learning in the presence of novel class instances (ATP, RR, XZF, JPA), pp. 2427–2435.

KDD-2015-FeldmanNPR #mining #online #predict

Utilizing Text Mining on Online Medical Forums to Predict Label Change due to Adverse Drug Reactions (RF, ON, AP, BR), pp. 1779–1788.

KDD-2015-KotziasDFS #using

From Group to Individual Labels Using Deep Features (DK, MD, NdF, PS), pp. 597–606.

KDD-2015-Papagiannopoulou #learning #multi

Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning (CP, GT, IT), pp. 915–924.

MLDM-2015-GovadaJMS #approach #hybrid #induction #learning #using

Hybrid Approach for Inductive Semi Supervised Learning Using Label Propagation and Support Vector Machine (AG, PJ, SM, SKS), pp. 199–213.

MLDM-2015-TreechalongRW #clustering #using

Semi-Supervised Stream Clustering Using Labeled Data Points (KT, TR, KW), pp. 281–295.

SIGIR-2015-Alonso #lessons learnt #quality #scalability

Practical Lessons for Gathering Quality Labels at Scale (OA), pp. 1089–1092.

REFSQ-2015-AliJPMM

The Emerging Requirement for Digital Addiction Labels (RA, NJ, KP, SM, JM), pp. 198–213.

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

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

SAC-2015-ReadPB #data type #learning

Deep learning in partially-labeled data streams (JR, FPC, AB), pp. 954–959.

RTA-2015-NageleZ

Certified Rule Labeling (JN, HZ), pp. 269–284.

DATE-2014-EusseLASLS #architecture #component #embedded #flexibility

A flexible ASIP architecture for connected components labeling in embedded vision applications (JFE, RL, GA, PS, BL, TS), pp. 1–6.

DRR-2014-ChachraXADT #documentation #image

Extraction and labeling high-resolution images from PDF documents (SKC, ZX, SA, DDF, GRT), p. ?–9.

HT-2014-ThomeeM #automation #equivalence

Automatic discovery of global and local equivalence relationships in labeled geo-spatial data (BT, GDFM), pp. 158–168.

SIGMOD-2014-AroraSB #graph #mining #statistics

Mining statistically significant connected subgraphs in vertex labeled graphs (AA, MS, AB), pp. 1003–1014.

VLDB-2014-JiangFWX #distance #network #query

Hop Doubling Label Indexing for Point-to-Point Distance Querying on Scale-Free Networks (MJ, AWCF, RCWW, YX), pp. 1203–1214.

VLDB-2014-SongCY0 #constraints

Repairing Vertex Labels under Neighborhood Constraints (SS, HC, JXY, LC), pp. 987–998.

VLDB-2014-WeiYLJ #approach #independence #permutation #query #reachability

Reachability Querying: An Independent Permutation Labeling Approach (HW, JXY, CL, RJ), pp. 1191–1202.

CSMR-WCRE-2014-XiaFLCW #behaviour #learning #multi #towards

Towards more accurate multi-label software behavior learning (XX, YF, DL, ZC, XW), pp. 134–143.

CIAA-2014-Fujiyoshi #automaton #multi #recognition

Recognition of Labeled Multidigraphs by Spanning Tree Automata (AF), pp. 188–199.

ICALP-v1-2014-AbrahamC #distance

Distance Labels with Optimal Local Stretch (IA, SC), pp. 52–63.

ICALP-v2-2014-AdjiashviliR #bound #graph

Labeling Schemes for Bounded Degree Graphs (DA, NR), pp. 375–386.

CHI-2014-BalataCM #2d #on the #using

On the selection of 2D objects using external labeling (JB, LC, ZM), pp. 2255–2258.

CHI-2014-DengRKBBF #multi #scalability

Scalable multi-label annotation (JD, OR, JK, MSB, ACB, FFL), pp. 3099–3102.

CHI-2014-KuleszaACFC #concept #evolution #machine learning

Structured labeling for facilitating concept evolution in machine learning (TK, SA, RC, DF, DXC), pp. 3075–3084.

HIMI-DE-2014-KimH14a #embedded #interactive

Label Embedded Treemapping: A Label Overlap Prevention Technique for Zoomable Treemaps and a User Interaction Technique (KK, JH), pp. 44–53.

CIKM-2014-HongBH #classification #framework #multi

A Mixtures-of-Trees Framework for Multi-Label Classification (CH, IB, MH), pp. 211–220.

CIKM-2014-PimplikarGBP #learning

Learning to Propagate Rare Labels (RP, DG, DB, GRP), pp. 201–210.

CIKM-2014-YeLQPM #generative

A Generative Model for Generating Relevance Labels from Human Judgments and Click-Logs (XY, JL, ZQ, BP, DM), pp. 1907–1910.

ECIR-2014-MarcheggianiTE0 #aspect-oriented #mining #multi #random

Hierarchical Multi-label Conditional Random Fields for Aspect-Oriented Opinion Mining (DM, OT, AE, FS), pp. 273–285.

ICML-c1-2014-LiL #classification #multi

Condensed Filter Tree for Cost-Sensitive Multi-Label Classification (CLL, HTL), pp. 423–431.

ICML-c1-2014-PinheiroC #network

Recurrent Convolutional Neural Networks for Scene Labeling (PHOP, RC), pp. 82–90.

ICML-c1-2014-Yu0KD #learning #multi #scalability

Large-scale Multi-label Learning with Missing Labels (HFY, PJ, PK, ISD), pp. 593–601.

ICML-c2-2014-ChakrabartiFCM #multi #network #scalability

Joint Inference of Multiple Label Types in Large Networks (DC, SF, JC, SAM), pp. 874–882.

ICML-c2-2014-FujiwaraI #performance

Efficient Label Propagation (YF, GI), pp. 784–792.

ICML-c2-2014-LinDH0 #classification #encoding #multi

Multi-label Classification via Feature-aware Implicit Label Space Encoding (ZL, GD, MH, JW), pp. 325–333.

ICML-c2-2014-LiuD #learning #problem #set

Learnability of the Superset Label Learning Problem (LPL, TGD), pp. 1629–1637.

ICML-c2-2014-ZhouLPM

Aggregating Ordinal Labels from Crowds by Minimax Conditional Entropy (DZ, QL, JCP, CM), pp. 262–270.

ICPR-2014-BertonL #graph #learning

Graph Construction Based on Labeled Instances for Semi-supervised Learning (LB, AdAL), pp. 2477–2482.

ICPR-2014-CabreraMS #bias

Systematic Labeling Bias: De-biasing Where Everyone is Wrong (GFC, CJM, JS), pp. 4417–4422.

ICPR-2014-El-GaalyTE #classification

Spatial-Visual Label Propagation for Local Feature Classification (TEG, MT, AME), pp. 3422–3427.

ICPR-2014-FanSCD #framework #learning #online #robust #taxonomy

A Unified Online Dictionary Learning Framework with Label Information for Robust Object Tracking (BF, JS, YC, YD), pp. 2311–2316.

ICPR-2014-GengWX #adaptation #estimation #learning

Facial Age Estimation by Adaptive Label Distribution Learning (XG, QW, YX), pp. 4465–4470.

ICPR-2014-GienTCL #fuzzy #learning #multi #predict

Dual Fuzzy Hypergraph Regularized Multi-label Learning for Protein Subcellular Location Prediction (JG, YYT, CLPC, YL), pp. 512–516.

ICPR-2014-KumarNJ #recognition

Face Recognition in Videos by Label Propagation (VK, AMN, CVJ), pp. 303–308.

ICPR-2014-LiDXWP #classification #image #probability

Local Label Probability Propagation for Hyperspectral Image Classification (HL, JD, SX, LW, CP), pp. 4251–4256.

ICPR-2014-TegenWHOJMNA #image #segmentation #semantics #using

Image Segmentation and Labeling Using Free-Form Semantic Annotation (AT, RW, LH, MO, FJ, DM, PN, KÅ), pp. 2281–2286.

ICPR-2014-WangSWB #consistency

Label Consistent Fisher Vectors for Supervised Feature Aggregation (QW, XS, MW, KLB), pp. 3588–3593.

ICPR-2014-WangT #classification

Label-Denoising Auto-encoder for Classification with Inaccurate Supervision Information (DW, XT), pp. 3648–3653.

ICPR-2014-WuLWHJ #learning #multi

Multi-label Learning with Missing Labels (BW, ZL, SW, BGH, QJ), pp. 1964–1968.

KDD-2014-Kushnir #adaptation #kernel #learning

Active-transductive learning with label-adapted kernels (DK), pp. 462–471.

KDD-2014-LiDDCZ #identification #process

Identifying and labeling search tasks via query-based hawkes processes (LL, HD, AD, YC, HZ), pp. 731–740.

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

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

KDD-2014-ZhouL #classification #mining #multi #network

Activity-edge centric multi-label classification for mining heterogeneous information networks (YZ, LL), pp. 1276–1285.

KR-2014-CeruttiGVZ #recursion

An SCC Recursive Meta-Algorithm for Computing Preferred Labellings in Abstract Argumentation (FC, MG, MV, MZ).

KR-2014-Dyrkolbotn #how #set #using

How to Argue for Anything: Enforcing Arbitrary Sets of Labellings using AFs (SKD).

MLDM-2014-AnanpiriyakulPV #classification #multi

Label Correction Strategy on Hierarchical Multi-Label Classification (TA, PP, PV), pp. 213–227.

SIGIR-2014-HingmireC #approach #classification #topic

Topic labeled text classification: a weakly supervised approach (SH, SC), pp. 385–394.

SIGIR-2014-NguyenL #microblog #network #on the #predict

On predicting religion labels in microblogging networks (MTN, EPL), pp. 1211–1214.

SIGIR-2014-RenPLDR #classification #multi #social

Hierarchical multi-label classification of social text streams (ZR, MHP, SL, WvD, MdR), pp. 213–222.

SIGIR-2014-RoitmanHS #approach #clustering

A fusion approach to cluster labeling (HR, SH, MSS), pp. 883–886.

SIGIR-2014-ZhangZ0LM #bibliography #classification #sentiment

Do users rate or review?: boost phrase-level sentiment labeling with review-level sentiment classification (YZ, HZ, MZ, YL, SM), pp. 1027–1030.

POPL-2014-HouCGT #logic #proving

Proof search for propositional abstract separation logics via labelled sequents (ZH, RC, RG, AT), pp. 465–476.

SAC-2014-RossiLR #algorithm #classification #network #using

A parameter-free label propagation algorithm using bipartite heterogeneous networks for text classification (RGR, AAL, SOR), pp. 79–84.

LICS-CSL-2014-ChenK #distance #markov #on the

On the total variation distance of labelled Markov chains (TC, SK), p. 10.

DocEng-2013-NourashrafeddinMA #clustering #documentation #interactive #using

Interactive text document clustering using feature labeling (SN, EEM, DVA), pp. 61–70.

DRR-2013-LipskyLN #policy

Optimal policy for labeling training samples (LL, DPL, GN).

DRR-2013-ZanibbiMV #graph #pattern matching #pattern recognition #recognition

Evaluating structural pattern recognition for handwritten math via primitive label graphs (RZ, HM, CVG).

ICDAR-2013-IwamuraTK #automation #database

Automatic Labeling for Scene Text Database (MI, MT, KK), pp. 1365–1369.

ICDAR-2013-MehriHGBM #approach

A Pixel Labeling Approach for Historical Digitized Books (MM, PH, PGK, AB, RM), pp. 817–821.

ICDAR-2013-ZhuZ #detection #image #recognition #using

Label Detection and Recognition for USPTO Images Using Convolutional K-Means Feature Quantization and Ada-Boost (SZ, RZ), pp. 633–637.

SIGMOD-2013-AkibaIY #distance #network #performance #query #scalability

Fast exact shortest-path distance queries on large networks by pruned landmark labeling (TA, YI, YY), pp. 349–360.

SIGMOD-2013-ChengHWF #graph #named #query #reachability #scalability

TF-Label: a topological-folding labeling scheme for reachability querying in a large graph (JC, SH, HW, AWCF), pp. 193–204.

SIGMOD-2013-FinisBK0FM #named #performance #version control

DeltaNI: an efficient labeling scheme for versioned hierarchical data (JF, RB, AK, TN, FF, NM), pp. 905–916.

VLDB-2013-FuWCW #distance #named #query

IS-LABEL: an Independent-Set based Labeling Scheme for Point-to-Point Distance Querying (AWCF, HW, JC, RCWW), pp. 457–468.

VLDB-2013-KhanWAY #graph #named #performance #similarity

NeMa: Fast Graph Search with Label Similarity (AK, YW, CCA, XY), pp. 181–192.

ICALP-v1-2013-BabenkoGGN #algorithm #optimisation

Algorithms for Hub Label Optimization (MAB, AVG, AG, VN), pp. 69–80.

ICALP-v1-2013-BulanekKS #on the #online #random

On Randomized Online Labeling with Polynomially Many Labels (JB, MK, MES), pp. 291–302.

ICALP-v2-2013-Janin #algebra #automaton #logic

Algebras, Automata and Logic for Languages of Labeled Birooted Trees (DJ), pp. 312–323.

CSCW-2013-LaseckiSKB #process #realtime #recognition

Real-time crowd labeling for deployable activity recognition (WSL, YCS, HAK, JPB), pp. 1203–1212.

HIMI-HSM-2013-HerronV #analysis #bibliography

Are Prescription Labels Usable? A Review and Analysis (MH, KPLV), pp. 252–260.

CIKM-2013-FangYZ #graph #scalability

Active exploration: simultaneous sampling and labeling for large graphs (MF, JY, XZ), pp. 829–834.

CIKM-2013-HanW #graph #mining #scalability

Mining frequent neighborhood patterns in a large labeled graph (JH, JRW), pp. 259–268.

CIKM-2013-LikhyaniB #estimation

Label constrained shortest path estimation (AL, SJB), pp. 1177–1180.

CIKM-2013-McDowellA #classification #network

Labels or attributes?: rethinking the neighbors for collective classification in sparsely-labeled networks (LM, DWA), pp. 847–852.

ECIR-2013-GligorovHOAS #evaluation #retrieval #video

An Evaluation of Labelling-Game Data for Video Retrieval (RG, MH, JvO, LA, GS), pp. 50–61.

ECIR-2013-MetrikovPA #consistency #nondeterminism #optimisation

Optimizing nDCG Gains by Minimizing Effect of Label Inconsistency (PM, VP, JAA), pp. 760–763.

ICML-c1-2013-LiWWT #fixpoint

Fixed-Point Model For Structured Labeling (QL, JW, DPW, ZT), pp. 214–221.

ICML-c1-2013-XiaoG #adaptation #probability #sequence

Domain Adaptation for Sequence Labeling Tasks with a Probabilistic Language Adaptation Model (MX, YG), pp. 293–301.

ICML-c2-2013-WestonMY #clustering #ranking #sublinear

Label Partitioning For Sublinear Ranking (JW, AM, HY), pp. 181–189.

ICML-c3-2013-BiK #classification #multi #performance

Efficient Multi-label Classification with Many Labels (WB, JTYK), pp. 405–413.

ICML-c3-2013-DembczynskiJKWH #approach #classification #multi #optimisation #plugin

Optimizing the F-Measure in Multi-Label Classification: Plug-in Rule Approach versus Structured Loss Minimization (KD, AJ, WK, WW, EH), pp. 1130–1138.

ICML-c3-2013-YuLKJC #learning

∝SVM for Learning with Label Proportions (FXY, DL, SK, TJ, SFC), pp. 504–512.

KDD-2013-AnchuriZBGS #approximate #graph #mining

Approximate graph mining with label costs (PA, MJZ, OB, SG, MS), pp. 518–526.

KDD-2013-KongCY #classification #correlation #mining #multi #network

Multi-label classification by mining label and instance correlations from heterogeneous information networks (XK, BC, PSY), pp. 614–622.

KDD-2013-WangS #classification #multi #relational #social #using

Multi-label relational neighbor classification using social context features (XW, GS), pp. 464–472.

SEKE-2013-LiLJJ #communication #comprehension #concurrent #debugging #graph

Locating and Understanding Concurrency Bugs Based on Edge-labeled Communication Graphs (S) (HL, ML, TJ, ZJ), pp. 525–530.

SIGIR-2013-HingmireCPC #classification #documentation #topic

Document classification by topic labeling (SH, SC, GKP, SC), pp. 877–880.

SIGIR-2013-MehrotraSBX #automation #microblog #modelling #topic #twitter

Improving LDA topic models for microblogs via tweet pooling and automatic labeling (RM, SS, WLB, LX), pp. 889–892.

QAPL-2013-Tranquilli

Indexed Labels for Loop Iteration Dependent Costs (PT), pp. 19–33.

SIGMOD-2012-JinRXL #approach #distance #graph #query #scalability

A highway-centric labeling approach for answering distance queries on large sparse graphs (RJ, NR, YX, VEL), pp. 445–456.

VLDB-2012-BaoDM #dependence #fine-grained #workflow

Labeling Workflow Views with Fine-Grained Dependencies (ZB, SBD, TM), pp. 1208–1219.

TACAS-2012-LangM #equation #lts #model checking #network #using

Partial Model Checking Using Networks of Labelled Transition Systems and Boolean Equation Systems (FL, RM), pp. 141–156.

ICPC-2012-LuciaPOPP #information retrieval #question #source code #using

Using IR methods for labeling source code artifacts: Is it worthwhile? (ADL, MDP, RO, AP, SP), pp. 193–202.

WCRE-2012-MediniAGPT #approach #execution #named

SCAN: An Approach to Label and Relate Execution Trace Segments (SM, GA, YGG, MDP, PT), pp. 135–144.

PEPM-2012-HamiltonJ #lts

Distillation with labelled transition systems (GWH, NDJ), pp. 15–24.

STOC-2012-AbrahamCG #approximate #distance #graph

Fully dynamic approximate distance oracles for planar graphs via forbidden-set distance labels (IA, SC, CG), pp. 1199–1218.

STOC-2012-BulanekKS #bound #online #problem

Tight lower bounds for the online labeling problem (JB, MK, MES), pp. 1185–1198.

ICALP-v1-2012-DinitzKR #approximate #scalability

Label Cover Instances with Large Girth and the Hardness of Approximating Basic k-Spanner (MD, GK, RR), pp. 290–301.

CSCW-2012-HsuJSC #framework #named #realtime #video

SynTag: a web-based platform for labeling real-time video (YCH, TJ, YTS, PCC), pp. 715–718.

ICEIS-v1-2012-CarvalhoBSR #clustering

Labeling Methods for Association Rule Clustering (VOdC, DSB, FFdS, SOR), pp. 105–111.

CIKM-2012-KazaiKM #crowdsourcing #quality

The face of quality in crowdsourcing relevance labels: demographics, personality and labeling accuracy (GK, JK, NMF), pp. 2583–2586.

CIKM-2012-LuZZX #image #learning #scalability #semantics #set

Semantic context learning with large-scale weakly-labeled image set (YL, WZ, KZ, XX), pp. 1859–1863.

CIKM-2012-MaoMZCYL #automation #topic

Automatic labeling hierarchical topics (XM, ZM, ZJZ, TSC, HY, XL), pp. 2383–2386.

CIKM-2012-PatwardhanBAMC

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

CIKM-2012-QiYZZ #mining #multi

Mining noisy tagging from multi-label space (ZQ, MY, Z(Z, ZZ), pp. 1925–1929.

CIKM-2012-ZhouCLZ #automation #topic

Exploring the existing category hierarchy to automatically label the newly-arising topics in cQA (GZ, LC, KL, JZ), pp. 1647–1651.

ECIR-2012-HosseiniCMKV #documentation #multi #on the

On Aggregating Labels from Multiple Crowd Workers to Infer Relevance of Documents (MH, IJC, NMF, GK, VV), pp. 182–194.

ECIR-2012-TholpadiDBS #clustering #corpus #multi #using

Cluster Labeling for Multilingual Scatter/Gather Using Comparable Corpora (GT, MKD, CB, SKS), pp. 388–400.

ICML-2012-KimKO #metric #parametricity #process #random #topic

Dirichlet Process with Mixed Random Measures: A Nonparametric Topic Model for Labeled Data (DK, SK, AHO), p. 90.

ICML-2012-LiuW #modelling #multi #probability

TrueLabel + Confusions: A Spectrum of Probabilistic Models in Analyzing Multiple Ratings (CL, YMW), p. 6.

ICML-2012-MalisiewiczSGE #detection #image #retrieval #visual notation

Exemplar-SVMs for Visual Ob ject Detection, Label Transfer and Image Retrieval (TM, AS, AG, AAE), p. 4.

ICML-2012-McDowellA #classification #hybrid

Semi-Supervised Collective Classification via Hybrid Label Regularization (LM, DWA), p. 162.

ICML-2012-MnihH #image #learning #semistructured data

Learning to Label Aerial Images from Noisy Data (VM, GEH), p. 31.

ICML-2012-YangMJZZ #kernel #learning #multi #probability #programming

Multiple Kernel Learning from Noisy Labels by Stochastic Programming (TY, MM, RJ, LZ, YZ), p. 21.

ICPR-2012-CaoL #categorisation #fuzzy

Type-2 fuzzy labeled latent Dirichlet allocation for human action categorization (XQC, ZQL), pp. 1338–1341.

ICPR-2012-CermanH #learning #problem

Tracking with context as a semi-supervised learning and labeling problem (LC, VH), pp. 2124–2127.

ICPR-2012-ElqurshE #video

Video figure ground labeling (AE, AME), pp. 2472–2475.

ICPR-2012-FangZ #learning

I don’t know the label: Active learning with blind knowledge (MF, XZ), pp. 2238–2241.

ICPR-2012-FefilatyevSKHGKDRB #reduction

Label-noise reduction with support vector machines (SF, MS, KK, LOH, DBG, RK, KD, AR, HB), pp. 3504–3508.

ICPR-2012-FiaschiKNH #learning

Learning to count with regression forest and structured labels (LF, UK, RN, FAH), pp. 2685–2688.

ICPR-2012-HeCS #algorithm #component

A new algorithm for labeling connected-components and calculating the Euler number, connected-component number, and hole number (LH, YC, KS), pp. 3099–3102.

ICPR-2012-JinGYZ #algorithm #learning #multi

Multi-label learning vector quantization algorithm (XBJ, GG, JY, DZ), pp. 2140–2143.

ICPR-2012-LiuCSTN #learning #multi #performance #problem #recursion #scalability

Recursive NMF: Efficient label tree learning for large multi-class problems (LL, PMC, SS, PNT, AN), pp. 2148–2151.

ICPR-2012-LoprestiN #automation

Optimal data partition for semi-automated labeling (DPL, GN), pp. 286–289.

ICPR-2012-PanLS #kernel #learning

Learning kernels from labels with ideal regularization (BP, JHL, LS), pp. 505–508.

ICPR-2012-PillaiFR #classification #multi #optimisation

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

ICPR-2012-ZhaoSS #learning #predict

Importance-weighted label prediction for active learning with noisy annotations (LZ, GS, RS), pp. 3476–3479.

KDD-2012-BodenGHS #graph #mining #multi

Mining coherent subgraphs in multi-layer graphs with edge labels (BB, SG, HH, TS), pp. 1258–1266.

KDD-2012-HuangYZ #multi #reuse

Multi-label hypothesis reuse (SJH, YY, ZHZ), pp. 525–533.

KDD-2012-YuDRZY #classification #multi #predict

Transductive multi-label ensemble classification for protein function prediction (GXY, CD, HR, GZ, ZY), pp. 1077–1085.

MLDM-2012-JiangLS #correlation #image #multi

Multi-label Image Annotation Based on Neighbor Pair Correlation Chain (GJ, XL, ZS), pp. 345–354.

SIGIR-2012-NiuGLC #evaluation #learning #rank #ranking

Top-k learning to rank: labeling, ranking and evaluation (SN, JG, YL, XC), pp. 751–760.

SAC-2012-CerriBC #algorithm #classification #multi #search-based

A genetic algorithm for Hierarchical Multi-Label Classification (RC, RCB, ACPLFdC), pp. 250–255.

SAC-2012-WickerPK #classification #composition #matrix #multi #using

Multi-label classification using boolean matrix decomposition (JW, BP, SK), pp. 179–186.

ICSE-2012-FengC #behaviour #learning #multi

Multi-label software behavior learning (YF, ZC), pp. 1305–1308.

IJCAR-2012-BaazLZ #calculus #effectiveness #semantics

Effective Finite-Valued Semantics for Labelled Calculi (MB, OL, AZ), pp. 52–66.

IJCAR-2012-SudaW

A PLTL-Prover Based on Labelled Superposition with Partial Model Guidance (MS, CW), pp. 537–543.

LICS-2012-CarayolS #automaton #effectiveness #equivalence #recursion #safety

Collapsible Pushdown Automata and Labeled Recursion Schemes: Equivalence, Safety and Effective Selection (AC, OS), pp. 165–174.

RTA-2012-Balabonski #axiom

Axiomatic Sharing-via-Labelling (TB), pp. 85–100.

TAP-2012-LeonHL #consistency

Conformance Relations for Labeled Event Structures (HPdL, SH, DL), pp. 83–98.

ICDAR-2011-KumarPD #classification #documentation #image #learning #multi #using

Document Image Classification and Labeling Using Multiple Instance Learning (JK, JP, DSD), pp. 1059–1063.

ICDAR-2011-NagyZ #image #interactive #named

CalliGUI: Interactive Labeling of Calligraphic Character Images (GN, XZ), pp. 977–981.

ICDAR-2011-VajdaJF #approach #learning

A Semi-supervised Ensemble Learning Approach for Character Labeling with Minimal Human Effort (SV, AJ, GAF), pp. 259–263.

ICDAR-2011-YouADGT #detection #using

Detecting Figure-Panel Labels in Medical Journal Articles Using MRF (DY, SA, DDF, VG, GRT), pp. 967–971.

SIGMOD-2011-BaoDM #on the fly #recursion #workflow

Labeling recursive workflow executions on-the-fly (ZB, SBD, TM), pp. 493–504.

FoSSaCS-2011-AristizabalBPPV #concurrent #constraints #programming #similarity

Deriving Labels and Bisimilarity for Concurrent Constraint Programming (AA, FB, CP, LFP, FDV), pp. 138–152.

CSMR-2011-SiddiqueM #clustering

Analyzing Term Weighting Schemes for Labeling Software Clusters (FS, OM), pp. 85–88.

PASTE-2011-JacobsonRM #library

Labeling library functions in stripped binaries (ERJ, NER, BPM), pp. 1–8.

ICALP-v2-2011-HermelinLWY #distance #graph

Distance Oracles for Vertex-Labeled Graphs (DH, AL, OW, RY), pp. 490–501.

HCI-DDA-2011-KimuraFKINOT #similarity

Appearance Similarity Index for Medicinal Ampoule Labels (MK, YF, AK, HI, KN, MO, FT), pp. 588–597.

HCI-DDA-2011-MoehrmannBSWH #image #scalability #set #usability

Improving the Usability of Hierarchical Representations for Interactively Labeling Large Image Data Sets (JM, SB, TS, GW, GH), pp. 618–627.

HCI-UA-2011-Furukawa #design #injection #question #what

What Label Design of Ampule for Injection, Do You Want? (HF), pp. 159–166.

CAiSE-2011-LeopoldMR #automation #modelling #on the #process

On the Automatic Labeling of Process Models (HL, JM, HAR), pp. 512–520.

ICEIS-v1-2011-RafeaSA #clustering #network #social

Label Oriented Clustering for Social Network Discussion Groups (AR, AEKS, SGA), pp. 205–210.

CIKM-2011-DaltonAS #retrieval #sequence

Passage retrieval for incorporating global evidence in sequence labeling (JD, JA, DAS), pp. 355–364.

CIKM-2011-DavisLMR #detection #graph

Detecting anomalies in graphs with numeric labels (MD, WL, PCM, GR), pp. 1197–1202.

CIKM-2011-FuLZZ #learning #query

Do they belong to the same class: active learning by querying pairwise label homogeneity (YF, BL, XZ, CZ), pp. 2161–2164.

CIKM-2011-GuLH #correlation #feature model #multi

Correlated multi-label feature selection (QG, ZL, JH), pp. 1087–1096.

CIKM-2011-KazaiKM #crowdsourcing

Worker types and personality traits in crowdsourcing relevance labels (GK, JK, NMF), pp. 1941–1944.

CIKM-2011-LiSL #network #people #social

Context-based people search in labeled social networks (CTL, MKS, SDL), pp. 1607–1612.

CIKM-2011-Nomoto #approach #documentation #named

WikiLabel: an encyclopedic approach to labeling documents en masse (TN), pp. 2341–2344.

CIKM-2011-SelvarajBSS #classification #dataset

Semi-supervised SVMs for classification with unknown class proportions and a small labeled dataset (SKS, BB, SS, SKS), pp. 653–662.

CIKM-2011-WangYQSW #web

Harvesting facts from textual web sources by constrained label propagation (YW, BY, LQ, MS, GW), pp. 837–846.

CIKM-2011-WangZLBW #classification #multi #random #using

Using random walks for multi-label classification (CW, WZ, ZL, YB, JW), pp. 2197–2200.

CIKM-2011-XuZYCXZ #constraints #graph #reachability #scalability

Answering label-constraint reachability in large graphs (KX, LZ, JXY, LC, YX, DZ), pp. 1595–1600.

CIKM-2011-YangZJ #graph #multi #named #query

DELTA: indexing and querying multi-labeled graphs (JY, SZ, WJ), pp. 1765–1774.

CIKM-2011-ZhuangLF #xml

Insert-friendly XML containment labeling scheme (CZ, ZL, SF), pp. 2449–2452.

ECIR-2011-KadarI #adaptation #categorisation

Domain Adaptation for Text Categorization by Feature Labeling (CK, JI), pp. 424–435.

ICML-2011-BiK #classification #multi

MultiLabel Classification on Tree- and DAG-Structured Hierarchies (WB, JTK), pp. 17–24.

KDD-2011-CerratoJG #classification #generative

Classification of proxy labeled examples for marketing segment generation (DC, RJ, AG), pp. 343–350.

KDD-2011-RamageMD #mining #modelling #topic

Partially labeled topic models for interpretable text mining (DR, CDM, STD), pp. 457–465.

KDD-2011-ZhangLS #learning

Serendipitous learning: learning beyond the predefined label space (DZ, YL, LS), pp. 1343–1351.

KDIR-2011-ZalikZ #algorithm #clustering #network

Network Clustering by Advanced Label Propagation Algorithm (KRZ, BZ), pp. 444–447.

KEOD-2011-SuzukiF #classification #documentation #multi #using

Multi-labeled Patent Document Classification using Technical Term Thesaurus (YS, FF), pp. 425–428.

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

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

SIGIR-2011-SandenZ #classification #multi #music

Enhancing multi-label music genre classification through ensemble techniques (CS, JZZ), pp. 705–714.

SIGIR-2011-WangHH #image #mining #search-based #web

Mining weakly labeled web facial images for search-based face annotation (DW, SCHH, YH), pp. 535–544.

RTA-2011-SternagelT #composition #semantics

Modular and Certified Semantic Labeling and Unlabeling (CS, RT), pp. 329–344.

RTA-2011-ZanklFM #diagrams

Labelings for Decreasing Diagrams (HZ, BF, AM), pp. 377–392.

CASE-2010-CabasinoGS #fault #petri net #using

Diagnosis using labeled Petri nets: Faults may either be silent or undistinguishable events (MPC, AG, CS), pp. 485–490.

SIGMOD-2010-BaoDKR #using #workflow

An optimal labeling scheme for workflow provenance using skeleton labels (ZB, SBD, SK, SR), pp. 711–722.

SIGMOD-2010-JinHWRX #constraints #database #graph #reachability

Computing label-constraint reachability in graph databases (RJ, HH, HW, NR, YX), pp. 123–134.

VLDB-2011-RiceT10 #graph #network #query #strict

Graph Indexing of Road Networks for Shortest Path Queries with Label Restrictions (MNR, VJT), pp. 69–80.

CIAA-2010-CimattiMRT #automaton #nondeterminism #regular expression

From Sequential Extended Regular Expressions to NFA with Symbolic Labels (AC, SM, MR, ST), pp. 87–94.

ICALP-v1-2010-GuruswamiKOPTW

SDP Gaps for 2-to-1 and Other Label-Cover Variants (VG, SK, RO, PP, MT, YW), pp. 617–628.

ICALP-v1-2010-MakarychevMS #algorithm #approximate #polynomial #problem #reduction

Maximum Quadratic Assignment Problem: Reduction from Maximum Label Cover and LP-Based Approximation Algorithm (KM, RM, MS), pp. 594–604.

ICALP-v2-2010-Fraigniaud

Informative Labeling Schemes (PF), p. 1.

CHI-2010-KelleyCBC #approach #online #privacy #standard

Standardizing privacy notices: an online study of the nutrition label approach (PGK, LC, JB, LFC), pp. 1573–1582.

CHI-2010-Rader #design

The effect of audience design on labeling, organizing, and finding shared files (ER), pp. 777–786.

SIGAda-2010-FongBLGWMW

Wouldn’t it be nice to have software labels (EF, PEB, RFL, SG, LW, GM, JW), pp. 31–32.

CIKM-2010-ChiHY

Mixture model label propagation (MC, XH, SY), pp. 1889–1892.

CIKM-2010-He #classification #learning #sentiment

Learning sentiment classification model from labeled features (YH), pp. 1685–1688.

CIKM-2010-LinC #classification #multi

Mr.KNN: soft relevance for multi-label classification (XL, XwC), pp. 349–358.

ICML-2010-BordesUW #ambiguity #learning #ranking #semantics

Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences (AB, NU, JW), pp. 103–110.

ICML-2010-ChengDH #ranking

Label Ranking Methods based on the Plackett-Luce Model (WC, KD, EH), pp. 215–222.

ICML-2010-HariharanZVV #classification #multi #scalability

Large Scale Max-Margin Multi-Label Classification with Priors (BH, LZM, SVNV, MV), pp. 423–430.

ICPR-2010-BollenbeckS #adaptation #segmentation

Joint Registration and Segmentation of Histological Volume Data by Diffusion-Based Label Adaption (FB, US), pp. 2440–2443.

ICPR-2010-ChiangK #approach

An Approach for Recognizing Text Labels in Raster Maps (YYC, CAK), pp. 3199–3202.

ICPR-2010-FrohlichRD #approach #image #performance

A Fast Approach for Pixelwise Labeling of Facade Images (BF, ER, JD), pp. 3029–3032.

ICPR-2010-HsinLLC #image #using

Image Inpainting Using Structure-Guided Priority Belief Propagation and Label Transformations (HFH, JJL, CSL, HYC), pp. 4492–4495.

ICPR-2010-JiaCLW #image #learning #performance

Efficient Learning to Label Images (KJ, LC, NL, LW), pp. 942–945.

ICPR-2010-SanromaAS #approach #graph #using

A Discrete Labelling Approach to Attributed Graph Matching Using SIFT Features (GS, RA, FS), pp. 954–957.

ICPR-2010-Williams #classification

Underwater Mine Classification with Imperfect Labels (DPW), pp. 4157–4161.

ICPR-2010-WuBT #image #predict

The Good, the Bad, and the Ugly: Predicting Aesthetic Image Labels (YW, CB, CT), pp. 1586–1589.

KDD-2010-AttenbergP #classification #learning #modelling #why

Why label when you can search?: alternatives to active learning for applying human resources to build classification models under extreme class imbalance (JA, FJP), pp. 423–432.

KDD-2010-ZhangZ #dependence #learning #multi

Multi-label learning by exploiting label dependency (MLZ, KZ), pp. 999–1008.

KDIR-2010-MuA #classification #graph #multi

Proximity-based Graph Embeddings for Multi-label Classification (TM, SA), pp. 74–84.

SIGIR-2010-AlfonsecaPR

Acquisition of instance attributes via labeled and related instances (EA, MP, ERA), pp. 58–65.

SIGIR-2010-MuhrKG #analysis #clustering

Analysis of structural relationships for hierarchical cluster labeling (MM, RK, MG), pp. 178–185.

SIGIR-2010-WhiteC

Exploring the use of labels to shortcut search trails (RWW, RC), pp. 811–812.

SIGIR-2010-YangMSM #low cost #quality

Collecting high quality overlapping labels at low cost (HY, AM, KMS, SM), pp. 459–466.

SAC-2010-AminBJ10a #wiki

Wikipedia driven autonomous label assignment in wrapper induced tables with missing column names (MSA, AB, HMJ), pp. 1656–1660.

SAC-2010-BaeAVNB #algorithm #performance #search-based

Convex onion peeling genetic algorithm: an efficient solution to map labeling of point-feature (WDB, SA, PV, SN, KYB), pp. 892–899.

RTA-2010-Aoto #automation #confluence #diagrams #proving

Automated Confluence Proof by Decreasing Diagrams based on Rule-Labelling (TA), pp. 7–16.

DocEng-2009-KohKB

Test collection management and labeling system (EK, AK, SB), pp. 39–42.

ICDAR-2009-SaundLS #documentation #image #named #user interface

PixLabeler: User Interface for Pixel-Level Labeling of Elements in Document Images (ES, JL, PS), pp. 646–650.

SIGMOD-2009-CorcoranSH #security #web

Cross-tier, label-based security enforcement for web applications (BJC, NS, MWH), pp. 269–282.

SIGMOD-2009-XuLWB #named #xml

DDE: from dewey to a fully dynamic XML labeling scheme (LX, TWL, HW, ZB), pp. 719–730.

MSR-2009-Kuhn #automation #component #evolution #source code #using #word

Automatic labeling of software components and their evolution using log-likelihood ratio of word frequencies in source code (AK), pp. 175–178.

ICALP-v2-2009-ColcombetZ #automaton #bound

A Tight Lower Bound for Determinization of Transition Labeled Büchi Automata (TC, KZ), pp. 151–162.

HCI-AUII-2009-VerhoefLBOZC #word

Bio-sensing for Emotional Characterization without Word Labels (TV, CLL, AB, FRO, TvdZ, FC), pp. 693–702.

IDGD-2009-ChenC #research

Application of the Labeled Magnitude Scale in Kansei Research (CYC, KC), pp. 219–227.

CIKM-2009-GardnerX #approach #automation #detection #sequence

Automatic link detection: a sequence labeling approach (JJG, LX), pp. 1701–1704.

CIKM-2009-KimPDG #classification #graph #web

Improving web page classification by label-propagation over click graphs (SMK, PP, LD, SG), pp. 1077–1086.

CIKM-2009-QiCKKW #learning

Combining labeled and unlabeled data with word-class distribution learning (YQ, RC, PPK, KK, JW), pp. 1737–1740.

CIKM-2009-ZhuWZ #learning

Label correspondence learning for part-of-speech annotation transformation (MZ, HW, JZ), pp. 1461–1464.

ECIR-2009-EsuliS #classification #learning #multi

Active Learning Strategies for Multi-Label Text Classification (AE, FS), pp. 102–113.

ICML-2009-ChengHH #learning #ranking

Decision tree and instance-based learning for label ranking (WC, JCH, EH), pp. 161–168.

ICML-2009-LiKZ #learning #using

Semi-supervised learning using label mean (YFL, JTK, ZHZ), pp. 633–640.

ICML-2009-QianJZHW #higher-order #random #sequence

Sparse higher order conditional random fields for improved sequence labeling (XQ, XJ, QZ, XH, LW), pp. 849–856.

KDD-2009-BeygelzimerL #learning

The offset tree for learning with partial labels (AB, JL), pp. 129–138.

KDD-2009-DonmezCS #learning

Efficiently learning the accuracy of labeling sources for selective sampling (PD, JGC, JGS), pp. 259–268.

KDD-2009-McGlohonBASF #detection #graph #named

SNARE: a link analytic system for graph labeling and risk detection (MM, SB, MGA, DMS, CF), pp. 1265–1274.

KDD-2009-OzonatY #classification #multi #statistics #towards #web

Towards a universal marketplace over the web: statistical multi-label classification of service provider forms with simulated annealing (KMO, DY), pp. 1295–1304.

KDD-2009-YangSWC #classification #effectiveness #learning #multi

Effective multi-label active learning for text classification (BY, JTS, TW, ZC), pp. 917–926.

KDIR-2009-BalujaRS #classification #graph #performance

Text Classification through Time — Efficient Label Propagation in Time-Based Graphs (SB, DR, DS), pp. 174–182.

SIGIR-2009-CarmelRZ #clustering #using #wiki

Enhancing cluster labeling using wikipedia (DC, HR, NZ), pp. 139–146.

SAC-2009-BaechlerBH #image #modelling #using #verification

Labeled images verification using Gaussian mixture models (MB, JLB, JH), pp. 1331–1335.

SAC-2009-HuangSMZH #approach #using

A new cross-training approach by using labeled data (DH, ES, GM, HZ, CCH), pp. 941–942.

CSL-2009-BlanquiR #on the #semantics #termination

On the Relation between Sized-Types Based Termination and Semantic Labelling (FB, CR), pp. 147–162.

DRR-2008-Schomaker #mining #word

Word mining in a sparsely labeled handwritten collection (LRBS), p. 68150.

VLDB-2008-NguyenNF #learning

Learning to extract form labels (HN, THN, JF), pp. 684–694.

STOC-2008-ManokaranNRS #metric #multi

Sdp gaps and ugc hardness for multiway cut, 0-extension, and metric labeling (RM, JN, PR, RS), pp. 11–20.

DLT-J-2007-DoyenHR08 #equivalence #markov

Equivalence of Labeled Markov Chains (LD, TAH, JFR), pp. 549–563.

ICALP-A-2008-FialaGK #complexity #distance #problem

Computational Complexity of the Distance Constrained Labeling Problem for Trees (Extended Abstract) (JF, PAG, JK), pp. 294–305.

ICGT-2008-ChalopinMM #graph #problem

Labelled (Hyper)Graphs, Negotiations and the Naming Problem (JC, AWM, YM), pp. 54–68.

ECIR-2008-LinC #category theory #evolution #network #social

Labeling Categories and Relationships in an Evolving Social Network (MSL, HHC), pp. 77–88.

ECIR-2008-MakrehchiK #automation #documentation

Automatic Extraction of Domain-Specific Stopwords from Labeled Documents (MM, MSK), pp. 222–233.

ECIR-2008-OfoghiYM #identification #natural language #semantics

The Impact of Semantic Class Identification and Semantic Role Labeling on Natural Language Answer Extraction (BO, JY, LM), pp. 430–437.

ICML-2008-KohliSRKT #multi #on the

On partial optimality in multi-label MRFs (PK, AS, CR, VK, PHST), pp. 480–487.

ICML-2008-QuadriantoSCL

Estimating labels from label proportions (NQ, AJS, TSC, QVL), pp. 776–783.

ICPR-2008-ChenCW #higher-order #named #performance #using

HOPS: Efficient region labeling using Higher Order Proxy Neighborhoods (AYCC, JJC, LW), pp. 1–4.

ICPR-2008-Ilic #recognition #using

Object labeling for recognition using vocabulary trees (SI), pp. 1–4.

ICPR-2008-TsuboiK #sequence

A new objective function for sequence labeling (YT, HK), pp. 1–4.

ICPR-2008-ZhangTJ #interactive

Interactive labeling of facial action units (LZ, YT, QJ), pp. 1–4.

ICPR-2008-ZhouCXQ #collaboration #image

Collaborative and content-based image labeling (NZ, WKC, XX, GQ), pp. 1–4.

KDD-2008-BilgicG #classification #effectiveness

Effective label acquisition for collective classification (MB, LG), pp. 43–51.

KDD-2008-GallagherTEF #classification #network #using

Using ghost edges for classification in sparsely labeled networks (BG, HT, TER, CF), pp. 256–264.

KDD-2008-JiTYY #classification #multi

Extracting shared subspace for multi-label classification (SJ, LT, SY, JY), pp. 381–389.

KDD-2008-NguyenC #classification

Classification with partial labels (NN, RC), pp. 551–559.

KDD-2008-ShengPI #data mining #mining #multi #quality #using

Get another label? improving data quality and data mining using multiple, noisy labelers (VSS, FJP, PGI), pp. 614–622.

KDD-2008-SimonKZ #agile #approach #reliability #scalability #set

Semi-supervised approach to rapid and reliable labeling of large data sets (GJS, VK, ZLZ), pp. 641–649.

KDD-2008-SunJY #classification #learning #multi

Hypergraph spectral learning for multi-label classification (LS, SJ, JY), pp. 668–676.

SIGIR-2008-AminiTG #algorithm #learning #ranking

A boosting algorithm for learning bipartite ranking functions with partially labeled data (MRA, TVT, CG), pp. 99–106.

SIGIR-2008-DruckMM #learning #using

Learning from labeled features using generalized expectation criteria (GD, GSM, AM), pp. 595–602.

SIGIR-2008-DuhK #learning #rank

Learning to rank with partially-labeled data (KD, KK), pp. 251–258.

SIGIR-2008-QuanCLX #adaptation #scalability #semantics

Adaptive label-driven scaling for latent semantic indexing (XQ, EC, QL, HX), pp. 827–828.

SIGIR-2008-TanWC #detection #sentiment #using

Combining learn-based and lexicon-based techniques for sentiment detection without using labeled examples (ST, YW, XC), pp. 743–744.

IJCAR-2008-FietzkeW

Labelled Splitting (AF, CW), pp. 459–474.

RTA-2008-SternagelM

Root-Labeling (CS, AM), pp. 336–350.

DRR-2007-ShettySBS #documentation #random #segmentation #using

Segmentation and labeling of documents using conditional random fields (SS, HS, MJB, SNS).

ICDAR-2007-BeusekomKSB #documentation #image #logic

Example-Based Logical Labeling of Document Title Page Images (JvB, DK, FS, TMB), pp. 919–923.

CIAA-J-2006-NicartCCGK07 #automaton #multi

Labelling Multi-Tape Automata with Constrained Symbol Classes (FN, JMC, TC, TG, AK), pp. 847–858.

ICALP-2007-KobayashiS #behaviour #calculus #type system

Undecidability of 2-Label BPP Equivalences and Behavioral Type Systems for the π -Calculus (NK, TS), pp. 740–751.

ICALP-2007-Korman

Labeling Schemes for Vertex Connectivity (AK), pp. 102–109.

HCI-AS-2007-Furukawa #challenge #effectiveness #fault #injection #question #what

Challenge for Preventing Medication Errors -Learn from Errors- : What Is the Most Effective Label Display to Prevent Medication Error for Injectable Drug ? (HF), pp. 437–442.

HCI-MIE-2007-SetiawanHL #interactive #multi #people #using

Multiple People Labeling and Tracking Using Stereo for Human Computer Interaction (NAS, SJH, CWL), pp. 738–746.

ICML-2007-Hanneke #bound #complexity #learning

A bound on the label complexity of agnostic active learning (SH), pp. 353–360.

ICML-2007-NguyenG #algorithm #sequence

Comparisons of sequence labeling algorithms and extensions (NN, YG), pp. 681–688.

KDD-2007-MeiSZ #automation #modelling #multi #topic

Automatic labeling of multinomial topic models (QM, XS, CZ), pp. 490–499.

KDD-2007-YanTS #classification #multi

Model-shared subspace boosting for multi-label classification (RY, JT, JRS), pp. 834–843.

MLDM-2007-LeeP #multi #on the #problem #reduction

On Applying Dimension Reduction for Multi-labeled Problems (ML, CHP), pp. 131–143.

PPDP-2007-Hamana #data type #higher-order #induction #semantics #type system

Higher-order semantic labelling for inductive datatype systems (MH), pp. 97–108.

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

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

SAC-2007-YapaK #algorithm #component #image

A connected component labeling algorithm for grayscale images and application of the algorithm on mammograms (RDY, HK), pp. 146–152.

CADE-2007-AntonsenW

A Labelled System for IPL with Variable Splitting (RA, AW), pp. 132–146.

CADE-2007-KoprowskiM #dependence #predict #satisfiability #using

Predictive Labeling with Dependency Pairs Using SAT (AK, AM), pp. 410–425.

CADE-2007-Lev-AmiWRS

Labelled Clauses (TLA, CW, TWR, MS), pp. 311–327.

VLDB-2006-DragutYM #interface #query

Meaningful Labeling of Integrated Query Interfaces (ECD, CTY, WM), pp. 679–690.

SAS-2006-PratikakisFH #reachability

Existential Label Flow Inference Via CFL Reachability (PP, JSF, MH), pp. 88–106.

STOC-2006-KarloffKMR #distance #metric #on the

On earthmover distance, metric labeling, and 0-extension (HJK, SK, AM, YR), pp. 547–556.

CIKM-2006-TomasicSZ

Processing information intent via weak labeling (AT, IS, JZ), pp. 856–857.

CIKM-2006-YangJZNX #clustering #documentation #ranking #using #validation

Document re-ranking using cluster validation and label propagation (LY, DHJ, GZ, NY, GX), pp. 690–697.

ICML-2006-GravesFGS #classification #network #sequence

Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks (AG, SF, FJG, JS), pp. 369–376.

ICML-2006-RavikumarL #estimation #markov #metric #polynomial #programming #random

Quadratic programming relaxations for metric labeling and Markov random field MAP estimation (PDR, JDL), pp. 737–744.

ICML-2006-WangZ #linear

Label propagation through linear neighborhoods (FW, CZ), pp. 985–992.

ICPR-v1-2006-OngB #clustering #learning

Learning Wormholes for Sparsely Labelled Clustering (EJO, RB), pp. 916–919.

ICPR-v2-2006-DhandraMHH #approach #detection #documentation #image

Skew Detection in Binary Image Documents Based on Image Dilation and Region labeling Approach (BVD, VSM, MH, RH), pp. 954–957.

ICPR-v2-2006-KimYK #robust

Background Robust Object Labeling by Voting of Weight-Aggregated Local Features (SK, KJY, ISK), pp. 219–222.

ICPR-v2-2006-LuXL #hybrid #recognition

A Hybrid Recognition Scheme Based on Partially Labeled SOM and MLP (SL, CX, YL), pp. 800–803.

ICPR-v3-2006-Law-ToGBB #behaviour #detection #video

Local Behaviours Labelling for Content Based Video Copy Detection (JLT, VGB, OB, NB), pp. 232–235.

ICPR-v4-2006-HerzogNKMOB #detection #image

Detection of presynaptic terminals on dendritic spines in double labeling confocal images (AH, RN, GK, BM, WO, KB), pp. 715–718.

KDD-2006-HashimotoAUKM #mining #order #performance #probability

A new efficient probabilistic model for mining labeled ordered trees (KH, KFAK, NU, MK, HM), pp. 177–186.

KDD-2006-ZhuNWZM #detection #web

Simultaneous record detection and attribute labeling in web data extraction (JZ, ZN, JRW, BZ, WYM), pp. 494–503.

SIGIR-2006-TreeratpitukC #automation #case study #clustering #statistics #using

An experimental study on automatically labeling hierarchical clusters using statistical features (PT, JPC), pp. 707–708.

SIGIR-2006-WuJ #framework #graph #learning #multi

A graph-based framework for relation propagation and its application to multi-label learning (MW, RJ), pp. 717–718.

QAPL-2005-DengCPP06 #metric

Metrics for Action-labelled Quantitative Transition Systems (YD, TC, CP, JP), pp. 79–96.

SAC-2006-HorvathHW #effectiveness #graph #induction

Effective rule induction from labeled graphs (TH, SH, SW), pp. 611–616.

IJCAR-2006-KoprowskiZ #automation #infinity #order #recursion #term rewriting

Automation of Recursive Path Ordering for Infinite Labelled Rewrite Systems (AK, HZ), pp. 332–346.

RTA-2006-HirokawaM #predict

Predictive Labeling (NH, AM), pp. 313–327.

ICDAR-2005-HadjarI #logic #using

Logical Labeling of Arabic Newspapers using Artificial Neural Nets (KH, RI), pp. 426–431.

ICDAR-2005-JournetERM #documentation

Text/Graphic labelling of Ancient Printed Documents (NJ, VE, JYR, RM), pp. 1010–1014.

STOC-2005-NaorS #metric

Balanced metric labeling (JN, RS), pp. 582–591.

ICALP-2005-CohenFIKP #automaton #finite #graph

Label-Guided Graph Exploration by a Finite Automaton (RC, PF, DI, AK, DP), pp. 335–346.

ICALP-2005-FialaGK #bound #distance #graph

Distance Constrained Labelings of Graphs of Bounded Treewidth (JF, PAG, JK), pp. 360–372.

CIKM-2005-GhamrawiM #classification #multi

Collective multi-label classification (NG, AM), pp. 195–200.

CIKM-2005-HeWYY #reachability

Compact reachability labeling for graph-structured data (HH, HW, JY, PSY), pp. 594–601.

CIKM-2005-LiL05a #encoding #named #novel #xml

QED: a novel quaternary encoding to completely avoid re-labeling in XML updates (CL, TWL), pp. 501–508.

CIKM-2005-LiLLY #on the #performance #xml

On reducing redundancy and improving efficiency of XML labeling schemes (CL, TWL, JL, TY), pp. 225–226.

ICML-2005-RamakrishnanCKB #approximate #classification

A model for handling approximate, noisy or incomplete labeling in text classification (GR, KPC, RK, PB), pp. 681–688.

ICML-2005-ZhouHS #graph #learning

Learning from labeled and unlabeled data on a directed graph (DZ, JH, BS), pp. 1036–1043.

KDD-2005-LangeB #probability

Combining partitions by probabilistic label aggregation (TL, JMB), pp. 147–156.

SIGIR-2005-BeitzelJFGLCK #automation #classification #query #using #web

Automatic web query classification using labeled and unlabeled training data (SMB, ECJ, OF, DAG, DDL, AC, AK), pp. 581–582.

SIGIR-2005-YuYT #multi #semantics

Multi-label informed latent semantic indexing (KY, SY, VT), pp. 258–265.

SIGIR-2005-ZhuJXG #classification #multi #using

Multi-labelled classification using maximum entropy method (SZ, XJ, WX, YG), pp. 274–281.

SOSP-2005-EfstathopoulosKVFZKMKM #operating system #process

Labels and event processes in the Asbestos operating system (PE, MNK, SV, CF, DZ, EK, DM, MFK, RM), pp. 17–30.

DRR-2004-MaoKT #design #documentation #evaluation #independence #performance

Style-independent document labeling: design and performance evaluation (SM, JK, GRT), pp. 14–22.

SIGMOD-2004-ChenHR #cost analysis

Cost-Based Labeling of Groups of Mass Spectra (LC, ZH, RR), pp. 167–178.

SIGMOD-2004-ONeilOPCSW #named #xml

ORDPATHs: Insert-Friendly XML Node Labels (PEO, EJO, SP, IC, GS, NW), pp. 903–908.

FoSSaCS-2004-MisloveOPW #markov #process

Duality for Labelled Markov Processes (MWM, JO, DP, JW), pp. 393–407.

CHI-2004-AhnD #game studies #image

Labeling images with a computer game (LvA, LD), pp. 319–326.

CIKM-2004-ChenL #clustering #dataset #named #scalability #visualisation

ClusterMap: labeling clusters in large datasets via visualization (KC, LL), pp. 285–293.

CIKM-2004-ChitrapuraK #graph #ranking

Node ranking in labeled directed graphs (KPC, SRK), pp. 597–606.

ICML-2004-Brinker #learning #ranking

Active learning of label ranking functions (KB).

ICML-2004-GaoWLC #approach #categorisation #learning #multi #robust

A MFoM learning approach to robust multiclass multi-label text categorization (SG, WW, CHL, TSC).

ICML-2004-KashimaT #algorithm #graph #kernel #learning #sequence

Kernel-based discriminative learning algorithms for labeling sequences, trees, and graphs (HK, YT).

ICML-2004-SuttonRM #modelling #probability #random #sequence

Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data (CAS, KR, AM).

ICPR-v1-2004-LiEFR #approach #multi #segmentation

A Multi-Label Front Propagation Approach for Object Segmentation (HL, AE, MJF, SR), pp. 600–603.

ICPR-v2-2004-ColleP #predict #process

Relaxation Labeling Processes for Protein Secondary Structure Prediction (GC, MP), pp. 355–358.

ICPR-v3-2004-Horiuchi #image #similarity

Similarity Measure of Labelled Images (TH), pp. 602–605.

ICPR-v3-2004-JuszczakD

Selective Sampling Based on the Variation in Label Assignments (PJ, RPWD), pp. 375–378.

ICPR-v3-2004-KangLTKX #keyword #video #visual notation

Visual Keywords Labeling in Soccer Video (YLK, JHL, QT, MSK, CX), pp. 850–853.

SIGIR-2004-DavidovGM #categorisation #dataset #generative

Parameterized generation of labeled datasets for text categorization based on a hierarchical directory (DD, EG, SM), pp. 250–257.

SAC-2004-Mosses #semantics

Exploiting labels in Structural Operational Semantics (PDM), pp. 1476–1481.

ICLP-2004-Barker #logic programming #source code

Labeled Logic Programs (SB), pp. 448–449.

LICS-2004-Huth #lts

Beyond Image-Finiteness: Labelled Transition Systems as a Stone Space (MH), pp. 222–231.

DRR-2003-KimLT #automation #online

Automated labeling of bibliographic data extracted from biomedical online journals (JK, DXL, GRT), pp. 47–56.

DRR-2003-LiangD #documentation #logic

Content features for logical document labeling (JL, DSD), pp. 189–196.

ICDAR-2003-AllierDGME #logic

Texture Feature Characterization for Logical Pre-labeling (BA, JD, AG, PM, HE), pp. 567–571.

ICDAR-2003-ChangC #algorithm #component #using

A Component-Labeling Algorithm Using Contour Tracing Technique (FC, CJC), pp. 741–745.

FoSSaCS-2003-CardelliGG

Manipulating Trees with Hidden Labels (LC, PG, GG), pp. 216–232.

ICALP-2003-BodirskyGK #generative #graph #random

Generating Labeled Planar Graphs Uniformly at Random (MB, CG, MK), pp. 1095–1107.

ICALP-2003-KormanP

Labeling Schemes for Weighted Dynamic Trees (AK, DP), pp. 369–383.

ICML-2003-KashimaTI #graph #kernel

Marginalized Kernels Between Labeled Graphs (HK, KT, AI), pp. 321–328.

MLDM-2003-ComiteGT #learning #multi

Learning Multi-label Alternating Decision Trees from Texts and Data (FDC, RG, MT), pp. 35–49.

ESEC-FSE-2003-UchitelKM #behaviour #lts #using

Behaviour model elaboration using partial labelled transition systems (SU, JK, JM), pp. 19–27.

LICS-2003-DanosD #approximate #markov #performance #process

Labelled Markov Processes: Stronger and Faster Approximations (VD, JD), pp. 341–350.

RTA-2003-AotoY #term rewriting #termination

Termination of Simply Typed Term Rewriting by Translation and Labelling (TA, TY), pp. 380–394.

CBSE-2002-MorenoHW #component #empirical #modelling #predict #standard #statistics #towards

Statistical Models for Empirical Component Properties and Assembly-Level Property Predictions: Toward Standard Labeling (GM, SH, KW), p. 10.

PODS-2002-CohenKM #xml

Labeling Dynamic XML Trees (EC, HK, TM), pp. 271–281.

TACAS-2002-Mateescu #calculus #lts #model checking #μ-calculus

Local Model-Checking of Modal μ-Calculus on Acyclic Labeled Transition Systems (RM), pp. 281–295.

ICALP-2002-BreugelSW #markov #process #testing

Testing Labelled Markov Processes (FvB, SS, JW), pp. 537–548.

ICML-2002-BockhorstC #concept

Exploiting Relations Among Concepts to Acquire Weakly Labeled Training Data (JB, MC), pp. 43–50.

ICML-2002-Ghani #categorisation #multi

Combining Labeled and Unlabeled Data for MultiClass Text Categorization (RG), pp. 187–194.

ICPR-v2-2002-RiviereMMTPF #graph #learning #markov #random #relational #using

Relational Graph Labelling Using Learning Techniques and Markov Random Fields (DR, JFM, JMM, FT, DPO, VF), pp. 172–175.

ICPR-v3-2002-LiangDMG #classification #logic

Page Classification through Logical Labelling (JL, DSD, MYM, JKG), pp. 477–480.

DATE-2001-HsiehCP #analysis #simulation

Microprocessor power analysis by labeled simulation (CTH, LC, MP), pp. 182–189.

ICDAR-2001-EglinG #documentation #functional #visual notation

Visual Exploration and Functional Document Labeling (VE, AG), pp. 816–820.

ICDAR-2001-Souafi-BensafiPLE #logic #network #using

Logical Labeling Using Bayesien Networks (SSB, MP, FL, HE), pp. 832–836.

CIKM-2001-AzcarragaY

Extracting Meaningful Labels for WEBSOM Text Archives (APA, TNYJ), pp. 41–48.

ICML-2001-BlumC #graph #learning #using

Learning from Labeled and Unlabeled Data using Graph Mincuts (AB, SC), pp. 19–26.

ICML-2001-IvanovBP

Expectation Maximization for Weakly Labeled Data (YAI, BB, AP), pp. 218–225.

ICML-2001-LaffertyMP #modelling #probability #random #sequence

Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data (JDL, AM, FCNP), pp. 282–289.

ICML-2001-LawrenceS #kernel

Estimating a Kernel Fisher Discriminant in the Presence of Label Noise (NDL, BS), pp. 306–313.

CSL-2001-Rasmussen #deduction #logic

Labelled Natural Deduction for Interval Logics (TMR), pp. 308–323.

LICS-2001-Jeffrey #induction #lts #type system

A Symbolic Labelled Transition System for Coinductive Subtyping of Fμ≤ Types (AJ), pp. 323–333.

IFM-2000-BertC #finite

Construction of Finite Labelled Transistion Systems from B Abstract Systems (DB, FC), pp. 235–254.

ICPR-v1-2000-LerasleDL #clique

Relaxation vs. Maximal Cliques Search for Projected Beams Labeling in a Structured Light Sensor (FL, MD, JML), pp. 1782–1785.

ICPR-v2-2000-MugurelVW #incremental #learning #multi #on the #recognition

On the Incremental Learning and Recognition of the Pattern of Movement of Multiple Labeled Objects in Dynamic Scenes (ML, SV, GAWW), pp. 2652–2655.

ICPR-v2-2000-SuzukiHS #component #performance

Fast Connected-Component Labeling Based on Sequential Local Operations in the Course of Forward Raster Scan Followed by Backward Raster Scan (KS, IH, NS), pp. 2434–2437.

ICPR-v3-2000-GarciaV #geometry #image

Acceleration of Thresholding and Labeling Operations through Geometric Processing of Gray-Level Images (MAG, BXV), pp. 3429–3432.

PADL-2000-BistarelliCGR #consistency #constraints #programming

Labeling and Partial Local Consistency for Soft Constraint Programming (SB, PC, YG, FR), pp. 230–248.

CSL-2000-OhsakiMG #equation #semantics #termination

Equational Termination by Semantic Labelling (HO, AM, JG), pp. 457–471.

LICS-2000-DesharnaisGJP #approximate #markov #process

Approximating Labeled Markov Processes (JD, VG, RJ, PP), pp. 95–106.

ICDAR-1999-PalmeroD #documentation #using

Structured Document Labeling and Rule Extraction using a New Recurrent Fuzzy-neural System (GISP, YAD), pp. 181–184.

CHI-1999-FeketeP #visualisation

Excentric Labeling: Dynamic Neighborhood Labeling for Data Visualization (JDF, CP), pp. 512–519.

CHI-1999-Soto #analysis #learning #quality #semantics

Learning and Performing by Exploration: Label Quality Measured by Latent Semantic Analysis (RS), pp. 418–425.

CHI-1999-YarinI #design #interactive #named #physics

TouchCounters: Designing Interactive Electronic Labels for Physical Containers (PY, HI), pp. 362–369.

ICPR-1998-HaritaogluHD #named #using

Ghost: a human body part labeling system using silhouettes (IH, DH, LSD), pp. 77–82.

ICPR-1998-MinMK #recognition #using

Recognition using labelled objects (SLM, JM, JK), pp. 1336–1338.

ICPR-1998-PalauS #approximate #classification #nearest neighbour #performance

The labelled cell classifier: a fast approximation to k nearest neighbors (AMP, RRS), pp. 823–827.

LICS-1998-DesharnaisEP #bisimulation #logic #markov #process

A Logical Characterization of Bisimulation for Labeled Markov Processes (JD, AE, PP), pp. 478–487.

ICDAR-1997-CesariniFGMSS97a #comprehension

Rectangle Labelling for an Invoice Understanding System (FC, EF, MG, SM, JS, GS), pp. 324–330.

ICALP-1997-Dami #fault #reduction #runtime

Labelled Reductions, Runtime Errors and Operational Subsumption (LD), pp. 782–793.

LICS-1997-BluteDEP #bisimulation #markov #process

Bisimulation for Labelled Markov Processes (RB, JD, AE, PP), pp. 149–158.

ICPR-1996-HaddonB #image #sequence

Spatio-temporal relaxation labelling applied to segmented infrared image sequences (JFH, JFB), pp. 171–175.

ICPR-1996-LiuTHS #adaptation #algorithm #documentation #geometry #segmentation

Adaptive document segmentation and geometric relation labeling: algorithms and experimental results (JL, YYT, QH, CYS), pp. 763–767.

ICPR-1996-PalmeroIDC #documentation #logic

A new neuro-fuzzy system for logical labeling of documents (GISP, JMCI, YAD, JLC), pp. 431–435.

ICPR-1996-PelilloF #learning #network

Autoassociative learning in relaxation labeling networks (MP, AMF), pp. 105–110.

ICPR-1996-ShaoK #fuzzy #multi

Fuzzy non-iterative ARG labeling with multiple interpretations (ZS, JK), pp. 181–185.

CADE-1996-MiddeldorpOZ #self #termination

Transforming Termination by Self-Labelling (AM, HO, HZ), pp. 373–387.

ICALP-1994-Breugel #lts

Generalized Finiteness Conditions of Labelled Transition Systems (FvB), pp. 376–387.

LFP-1994-ClingerH #compilation #optimisation

λ, the Ultimate Label or a Simple Optimizing Compiler for Scheme (WDC, LTH), pp. 128–139.

POPL-1994-GarrigueA #polymorphism #λ-calculus

The Typed Polymorphic Label-Selective λ-Calculus (JG, HAK), pp. 35–47.

ICDAR-1993-BelaidA #approach #documentation

A labeling approach for mixed document blocks (AB, OTA), pp. 749–752.

ICDAR-1993-HoriuchiTYYI #optimisation #problem

Generalized interpretation of optimization methods for labeling problems (TH, KT, HY, KY, TI), pp. 6–9.

RTA-1993-AspertiL #λ-calculus

Paths, Computations and Labels in the λ-Calculus (AA, CL), pp. 152–167.

CAV-1990-LloretAV #communication #composition #design #petri net #protocol #using #verification

Compositional Design and Verification of Communication Protocols, Using Labelled Petri Nets (JCL, PA, FV), pp. 96–105.

LICS-1988-Winskel #composition #petri net #proving

A Category of Labelled Petri Nets and Compositional Proof System (Extended Abstract) (GW), pp. 142–154.

GG-1986-BoerL #comparison

Map OL-systems with edge label control: Comparison of marker and cyclic systems (MJMdB, AL), pp. 378–392.

GG-1986-MainR #graph grammar

Fundamentals of edge-label controlled graph grammars (MGM, GR), pp. 411–426.

STOC-1983-BabaiL #canonical #graph

Canonical Labeling of Graphs (LB, EML), pp. 171–183.

GG-1982-JanssensR82a #graph grammar

Graph grammars with node-label controlled rewriting and embedding (DJ, GR), pp. 186–205.

POPL-1980-Weihl #analysis #data flow #interprocedural #pointer

Interprocedural Data Flow Analysis in the Presence of Pointers, Procedure Variables and Label Variables (WEW), pp. 83–94.

POPL-1973-Schkolnick #parsing #precedence

Labelled Precedence Parsing (MS), pp. 33–40.