Theory

High-Dimensional Learning of Linear Causal Networks via Inverse Covariance Estimation JMLR 2014 How hard is my MDP?" The distribution-norm to the rescue" NeurIPS 2014 Incremental Clustering: The Case for Extra Clusters NeurIPS 2014 Latent Bandits. ICML 2014 Learning on graphs using Orthonormal Representation is Statistically Consistent NeurIPS 2014 Learning with Fredholm Kernels NeurIPS 2014 lil’ UCB : An Optimal Exploration Algorithm for Multi-Armed Bandits COLT 2014 Local Linear Convergence of Forward--Backward under Partial Smoothness NeurIPS 2014 Lower Bounds on the Performance of Polynomial-time Algorithms for Sparse Linear Regression COLT 2014 Multivariate f-divergence Estimation With Confidence NeurIPS 2014 Near-optimal sample compression for nearest neighbors NeurIPS 2014 New Results for Random Walk Learning JMLR 2014 Nonnegative Sparse PCA with Provable Guarantees ICML 2014 Online Clustering of Bandits ICML 2014 On Measure Concentration of Random Maximum A-Posteriori Perturbations ICML 2014 On Projective Reconstruction In Arbitrary Dimensions CVPR 2014 On the Computational Efficiency of Training Neural Networks NeurIPS 2014 On the Number of Linear Regions of Deep Neural Networks NeurIPS 2014 On the Statistical Consistency of Plug-in Classifiers for Non-decomposable Performance Measures NeurIPS 2014 Optimal decision-making with time-varying evidence reliability NeurIPS 2014 Optimal rates for k-NN density and mode estimation NeurIPS 2014 PAC-Bayesian Collective Stability AISTATS 2014 Persistence-based Structural Recognition CVPR 2014 Projecting Markov Random Field Parameters for Fast Mixing NeurIPS 2014 Provable Tensor Factorization with Missing Data NeurIPS 2014