← Optimization & Theory
Machine Learning › Optimization & Theory ›

Statistics

684 directly classified papers

Papers per year

Papers

A General Framework for Consistency of Principal Component Analysis JMLR 2016
Optimal Estimation of Derivatives in Nonparametric Regression JMLR 2016
Guarding against Spurious Discoveries in High Dimensions JMLR 2016
Efficient Nonparametric Smoothness Estimation NIPS 2016
Learning from Survey Training Samples: Rate Bounds for Horvitz-Thompson Risk Minimizers ACML 2016
Principal Differences Analysis: Interpretable Characterization of Differences between Distributions NIPS 2015
Measuring Sample Quality with Stein's Method NIPS 2015
Competitive Distribution Estimation: Why is Good-Turing Good NIPS 2015
Nonparametric von Mises Estimators for Entropies, Divergences and Mutual Informations NIPS 2015
Optimal Ridge Detection using Coverage Risk NIPS 2015
Sufficient Dimension Reduction via Direct Estimation of the Gradients of Logarithmic Conditional Densities ACML 2015
The Likelihood-Ratio Test and Efficient Robust Estimation ICCV 2015
Consistent estimation of dynamic and multi-layer block models ICML 2015
Statistical Model Criticism using Kernel Two Sample Tests NIPS 2015
On the consistency theory of high dimensional variable screening NIPS 2015
Testing Closeness With Unequal Sized Samples NIPS 2015
Mixing Time Estimation in Reversible Markov Chains from a Single Sample Path NIPS 2015
Localized Complexities for Transductive Learning COLT 2014
Elementary Estimators for Sparse Covariance Matrices and other Structured Moments ICML 2014
Maximum Mean Discrepancy for Class Ratio Estimation: Convergence Bounds and Kernel Selection ICML 2014
Computing Parametric Ranking Models via Rank-Breaking ICML 2014
Kernel Mean Estimation via Spectral Filtering NIPS 2014
Consistency of weighted majority votes NIPS 2014
Quantized Estimation of Gaussian Sequence Models in Euclidean Balls NIPS 2014
Near-Optimal-Sample Estimators for Spherical Gaussian Mixtures NIPS 2014