learning theory

Learning Probability Measures with respect to Optimal Transport Metrics NeurIPS 2012 Learning Valuation Functions COLT 2012 Mixability in Statistical Learning NeurIPS 2012 New Bounds for Learning Intervals with Implications for Semi-Supervised Learning COLT 2012 On Ranking and Generalization Bounds JMLR 2012 On the Convergence Rate of -Norm Multiple Kernel Learning JMLR 2012 On the Necessity of Irrelevant Variables JMLR 2012 Pointwise Tracking the Optimal Regression Function NeurIPS 2012 Statistical Consistency of Ranking Methods in A Rank-Differentiable Probability Space NeurIPS 2012 Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions NeurIPS 2012 Towards a learning-theoretic analysis of spike-timing dependent plasticity NeurIPS 2012 Agnostic KWIK learning and efficient approximate reinforcement learning COLT 2011 Agnostic Selective Classification NeurIPS 2011 Complexity-Based Approach to Calibration with Checking Rules COLT 2011 Learning large-margin halfspaces with more malicious noise NeurIPS 2011 Lower Bounds for Passive and Active Learning NeurIPS 2011 Missing Information Impediments to Learnability COLT 2011 Multiclass Learnability and the ERM principle COLT 2011 On NDCG Consistency of Listwise Ranking Methods AISTATS 2011 Smoothness, Disagreement Coefficient, and the Label Complexity of Agnostic Active Learning JMLR 2011 Statistical Tests for Optimization Efficiency NeurIPS 2011 The Local Rademacher Complexity of Lp-Norm Multiple Kernel Learning NeurIPS 2011 A Theory of Multiclass Boosting NeurIPS 2010 Empirical Bernstein Inequalities for U-Statistics NeurIPS 2010 Learning Bounds for Importance Weighting NeurIPS 2010