Supervised Learning

Learning to translate from graded and negative relevance information COLING 2016 Logistic Boosting Regression for Label Distribution Learning CVPR 2016 On Construction of Hybrid Logistic Regression-Naïve Bayes Model for Classification PGM 2016 On Discriminative Framework for Single Channel Audio Source Separation Interspeech 2016 Predicting the Evocation Relation between Lexicalized Concepts COLING 2016 Protein contact prediction from amino acid co-evolution using convolutional networks for graph-valued images NeurIPS 2016 Says Who…? Identification of Expert versus Layman Critics’ Reviews of Documentary Films COLING 2016 Selection of Multi-Genre Broadcast Data for the Training of Automatic Speech Recognition Systems Interspeech 2016 Staple: Complementary Learners for Real-Time Tracking CVPR 2016 Supervised learning through the lens of compression NeurIPS 2016 Support Vector Hazards Machine: A Counting Process Framework for Learning Risk Scores for Censored Outcomes JMLR 2016 The Teaching Dimension of Linear Learners JMLR 2016 Attribute Efficient Linear Regression with Distribution-Dependent Sampling ICML 2015 Classifier Learning With Hidden Information CVPR 2015 Conditional High-Order Boltzmann Machine: A Supervised Learning Model for Relation Learning ICCV 2015 Consistency of structured output learning with missing labels ACML 2015 Continuous Target Shift Adaptation in Supervised Learning ACML 2015 Deep LAC: Deep Localization, Alignment and Classification for Fine-Grained Recognition CVPR 2015 Efficient Second-Order Gradient Boosting for Conditional Random Fields AISTATS 2015 End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture NeurIPS 2015 Enforcing balance allows local supervised learning in spiking recurrent networks NeurIPS 2015 Fixation Bank: Learning to Reweight Fixation Candidates CVPR 2015 From Dependency to Causality: A Machine Learning Approach JMLR 2015 Learning Fast-Mixing Models for Structured Prediction ICML 2015 Learning from Corrupted Binary Labels via Class-Probability Estimation ICML 2015