supervised learning

Gibbs Max-Margin Topic Models with Fast Sampling Algorithms ICML 2013 GURLS: A Least Squares Library for Supervised Learning JMLR 2013 How to Solve Classification and Regression Problems on High-Dimensional Data with a Supervised Extension of Slow Feature Analysis JMLR 2013 Large-Scale Bandit Problems and KWIK Learning ICML 2013 Learning Structured Low-Rank Representations for Image Classification CVPR 2013 Nonparametric Sparsity and Regularization JMLR 2013 Perceiving, Learning, and Exploiting Object Affordances for Autonomous Pile Manipulation RSS 2013 Salient Object Detection: A Discriminative Regional Feature Integration Approach CVPR 2013 Vanishing Component Analysis ICML 2013 Active Learning from Multiple Knowledge Sources AISTATS 2012 A Ranking-based KNN Approach for Multi-Label Classification ACML 2012 Deep Spatio-Temporal Architectures and Learning for Protein Structure Prediction NeurIPS 2012 Latent Coincidence Analysis: A Hidden Variable Model for Distance Metric Learning NeurIPS 2012 Local Supervised Learning through Space Partitioning NeurIPS 2012 Monte Carlo Methods for Maximum Margin Supervised Topic Models NeurIPS 2012 Multi-Instance Learning with Any Hypothesis Class JMLR 2012 Supervised Dimension Reduction with Topic Models ACML 2012 Supervised Learning with Similarity Functions NeurIPS 2012 Contextual Bandit Algorithms with Supervised Learning Guarantees AISTATS 2011 Discussion of “Contextual Bandit Algorithms with Supervised Learning Guarantees” AISTATS 2011 Learning to Search Efficiently in High Dimensions NeurIPS 2011 Sequential Event Prediction with Association Rules COLT 2011 ShareBoost: Efficient multiclass learning with feature sharing NeurIPS 2011 Agnostic Active Learning Without Constraints NeurIPS 2010 A New Probabilistic Model for Rank Aggregation NeurIPS 2010