statistical learning

A Finite Sample Analysis of the Naive Bayes Classifier JMLR 2015 Agnostic Insurability of Model Classes JMLR 2015 Compositional Hierarchical Representation of Shape Manifolds for Classification of Non-Manifold Shapes ICCV 2015 Convergence Rates of Active Learning for Maximum Likelihood Estimation NeurIPS 2015 Distributionally Robust Logistic Regression NeurIPS 2015 Learning with a Wasserstein Loss NeurIPS 2015 Learning with Incremental Iterative Regularization NeurIPS 2015 Learning with Square Loss: Localization through Offset Rademacher Complexity COLT 2015 MRA-based Statistical Learning from Incomplete Rankings ICML 2015 On the Pseudo-Dimension of Nearly Optimal Auctions NeurIPS 2015 Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters NeurIPS 2015 Risk and Regret of Hierarchical Bayesian Learners ICML 2015 Testing Closeness With Unequal Sized Samples NeurIPS 2015 The Ladder: A Reliable Leaderboard for Machine Learning Competitions ICML 2015 The Sample Complexity of Learning Linear Predictors with the Squared Loss JMLR 2015 Variable Selection is Hard COLT 2015 Active Regression by Stratification NeurIPS 2014 A New Perspective on Learning Linear Separators with Large L_qL_p Margins AISTATS 2014 A Unified Framework for Consistency of Regularized Loss Minimizers ICML 2014 Consistency of weighted majority votes NeurIPS 2014 Estimation with Norm Regularization NeurIPS 2014 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 Multivariate Maximal Correlation Analysis ICML 2014