Statistics

On Communication Cost of Distributed Statistical Estimation and Dimensionality NeurIPS 2014 Optimal rates for k-NN density and mode estimation NeurIPS 2014 Quantized Estimation of Gaussian Sequence Models in Euclidean Balls NeurIPS 2014 Sparse PCA via Covariance Thresholding NeurIPS 2014 Using Projection Kurtosis Concentration Of Natural Images For Blind Noise Covariance Matrix Estimation CVPR 2014 A Kernel Test for Three-Variable Interactions NeurIPS 2013 B-test: A Non-parametric, Low Variance Kernel Two-sample Test NeurIPS 2013 CODA: High Dimensional Copula Discriminant Analysis JMLR 2013 Complexity Theoretic Lower Bounds for Sparse Principal Component Detection COLT 2013 Consistency of Robust Kernel Density Estimators COLT 2013 Density estimation from unweighted k-nearest neighbor graphs: a roadmap NeurIPS 2013 Estimating LASSO Risk and Noise Level NeurIPS 2013 Estimating the Unseen: Improved Estimators for Entropy and other Properties NeurIPS 2013 Generalized Method-of-Moments for Rank Aggregation NeurIPS 2013 Generalizing Analytic Shrinkage for Arbitrary Covariance Structures NeurIPS 2013 Horizon-Independent Optimal Prediction with Log-Loss in Exponential Families COLT 2013 Local Privacy and Minimax Bounds: Sharp Rates for Probability Estimation NeurIPS 2013 Minimax Theory for High-dimensional Gaussian Mixtures with Sparse Mean Separation NeurIPS 2013 Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition NeurIPS 2013 New Subsampling Algorithms for Fast Least Squares Regression NeurIPS 2013 On model selection consistency of penalized M-estimators: a geometric theory NeurIPS 2013 PAC-Bayes-Empirical-Bernstein Inequality NeurIPS 2013 Robust Sparse Principal Component Regression under the High Dimensional Elliptical Model NeurIPS 2013 Sparse Inverse Covariance Estimation with Calibration NeurIPS 2013 Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. NeurIPS 2013