Learning Theory

Efficient Compressive Phase Retrieval with Constrained Sensing Vectors NeurIPS 2015 Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction NeurIPS 2015 Efficient Learning of Linear Separators under Bounded Noise COLT 2015 Entropy-Based Concentration Inequalities for Dependent Variables ICML 2015 Estimation from Pairwise Comparisons: Sharp Minimax Bounds with Topology Dependence AISTATS 2015 Evaluating the statistical significance of biclusters NeurIPS 2015 Exceptional Rotations of Random Graphs: A VC Theory JMLR 2015 Exp-Concavity of Proper Composite Losses COLT 2015 Explore no more: Improved high-probability regret bounds for non-stochastic bandits NeurIPS 2015 Fast Classification Rates for High-dimensional Gaussian Generative Models NeurIPS 2015 Fast Convergence of Regularized Learning in Games NeurIPS 2015 Faster Algorithms for Testing under Conditional Sampling COLT 2015 Fast Rates for Exp-concave Empirical Risk Minimization NeurIPS 2015 Fast Rates in Statistical and Online Learning JMLR 2015 Feature Selection for Linear SVM with Provable Guarantees AISTATS 2015 Finite-Time Analysis of Projected Langevin Monte Carlo NeurIPS 2015 First-order regret bounds for combinatorial semi-bandits COLT 2015 Following the Perturbed Leader for Online Structured Learning ICML 2015 Generalization error bounds for learning to rank: Does the length of document lists matter? ICML 2015 Generalization in Adaptive Data Analysis and Holdout Reuse NeurIPS 2015 Hierarchies of Relaxations for Online Prediction Problems with Evolving Constraints COLT 2015 How Hard is Inference for Structured Prediction? ICML 2015 Improved Regret Bounds for Undiscounted Continuous Reinforcement Learning ICML 2015 Improved Sum-of-Squares Lower Bounds for Hidden Clique and Hidden Submatrix Problems COLT 2015 Interactive Fingerprinting Codes and the Hardness of Preventing False Discovery COLT 2015