learning theory

From Stochastic Mixability to Fast Rates NeurIPS 2014 Fundamental Limits of Online and Distributed Algorithms for Statistical Learning and Estimation NeurIPS 2014 Learning without concentration COLT 2014 Low-Rank Spectral Learning AISTATS 2014 Multivariate f-divergence Estimation With Confidence NeurIPS 2014 Near-optimal sample compression for nearest neighbors NeurIPS 2014 PAC-Bayesian Collective Stability AISTATS 2014 PAC-Bayesian Theory for Transductive Learning AISTATS 2014 Sample Compression for Multi-label Concept Classes COLT 2014 Sparse Polynomial Learning and Graph Sketching NeurIPS 2014 The Complexity of Learning Halfspaces using Generalized Linear Methods COLT 2014 A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers ICML 2013 Collective Stability in Structured Prediction: Generalization from One Example ICML 2013 Cost-sensitive Multiclass Classification Risk Bounds ICML 2013 Distribution-Free Distribution Regression AISTATS 2013 Efficient Learning of Simplices COLT 2013 Learning Using Local Membership Queries COLT 2013 On model selection consistency of penalized M-estimators: a geometric theory NeurIPS 2013 PAC-Bayes-Empirical-Bernstein Inequality NeurIPS 2013 Passive Learning with Target Risk COLT 2013 Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction ICML 2013 Statistical Active Learning Algorithms NeurIPS 2013 The Sample-Complexity of General Reinforcement Learning ICML 2013 Computational Bounds on Statistical Query Learning COLT 2012 Generalization Bounds for Domain Adaptation NeurIPS 2012