Learning Theory

On the Generalization Ability of Online Learning Algorithms for Pairwise Loss Functions ICML 2013 On the Learnability of Shuffle Ideals JMLR 2013 On the Relationship Between Binary Classification, Bipartite Ranking, and Binary Class Probability Estimation NeurIPS 2013 On the Representational Efficiency of Restricted Boltzmann Machines NeurIPS 2013 On the Sample Complexity of Subspace Learning NeurIPS 2013 Open Problem: Adversarial Multiarmed Bandits with Limited Advice COLT 2013 Optimal Discovery with Probabilistic Expert Advice: Finite Time Analysis and Macroscopic Optimality JMLR 2013 Optimal rates for stochastic convex optimization under Tsybakov noise condition ICML 2013 PAC-Bayes-Empirical-Bernstein Inequality NeurIPS 2013 Passive Learning with Target Risk COLT 2013 Predictive PAC Learning and Process Decompositions NeurIPS 2013 Prior-free and prior-dependent regret bounds for Thompson Sampling NeurIPS 2013 Regret Minimization for Branching Experts COLT 2013 Regularization of Neural Networks using DropConnect ICML 2013 Reinforcement Learning in Robust Markov Decision Processes NeurIPS 2013 Representation, Approximation and Learning of Submodular Functions Using Low-rank Decision Trees COLT 2013 Risk Bounds and Learning Algorithms for the Regression Approach to Structured Output Prediction ICML 2013 Sharp analysis of low-rank kernel matrix approximations COLT 2013 Sharp Generalization Error Bounds for Randomly-projected Classifiers ICML 2013 Sparse Adaptive Dirichlet-Multinomial-like Processes COLT 2013 Sparsity-Based Generalization Bounds for Predictive Sparse Coding ICML 2013 Sparsity Regret Bounds for Individual Sequences in Online Linear Regression JMLR 2013 Stability and Hypothesis Transfer Learning ICML 2013 Statistical Active Learning Algorithms NeurIPS 2013 The Fast Convergence of Incremental PCA NeurIPS 2013