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Multi-Label Classification

401 directly classified papers

Papers per year

Papers

Multi-scale and Discriminative Part Detectors Based Features for Multi-label Image Classification IJCAI 2018
LanideNN: Multilingual Language Identification on Character Window EACL 2017
An Easy-to-hard Learning Paradigm for Multiple Classes and Multiple Labels JMLR 2017
Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification NIPS 2017
Multilabel Classification with Group Testing and Codes ICML 2017
Target Curricula via Selection of Minimum Feature Sets: a Case Study in Boolean Networks JMLR 2017
Gradient Boosted Decision Trees for High Dimensional Sparse Output ICML 2017
A Unified View of Multi-Label Performance Measures ICML 2017
Confidence Sets with Expected Sizes for Multiclass Classification JMLR 2017
Recognizing Emotions From Abstract Paintings Using Non-Linear Matrix Completion CVPR 2016
Structured Prediction Energy Networks ICML 2016
Multi-Label Ranking From Positive and Unlabeled Data CVPR 2016
PD-Sparse : A Primal and Dual Sparse Approach to Extreme Multiclass and Multilabel Classification ICML 2016
Logistic Boosting Regression for Label Distribution Learning CVPR 2016
Political News Sentiment Analysis for Under-resourced Languages COLING 2016
Conditional Bernoulli Mixtures for Multi-label Classification ICML 2016
A Bayesian Nonparametric Approach for Multi-label Classification ACML 2016
Multi-Label Classification with Cutset Networks PGM 2016
Counterfactual Risk Minimization: Learning from Logged Bandit Feedback ICML 2015
Learning Graph Structure for Multi-Label Image Classification via Clique Generation CVPR 2015
Joint Patch and Multi-Label Learning for Facial Action Unit Detection CVPR 2015
Learning with a Wasserstein Loss NIPS 2015
Multi-instance multi-label learning in the presence of novel class instances ICML 2015
On the Optimality of Multi-Label Classification under Subset Zero-One Loss for Distributions Satisfying the Composition Property ICML 2015
Multilabel Structured Output Learning with Random Spanning Trees of Max-Margin Markov Networks NIPS 2014