Statistics

QUIC: Quadratic Approximation for Sparse Inverse Covariance Estimation JMLR 2014 Recovering Distributions from Gaussian RKHS Embeddings AISTATS 2014 Robust Inverse Covariance Estimation under Noisy Measurements ICML 2014 Robust Kernel Density Estimation by Scaling and Projection in Hilbert Space NeurIPS 2014 Sparse PCA via Covariance Thresholding NeurIPS 2014 Sparsity and the Truncated l^2-norm AISTATS 2014 Square Deal: Lower Bounds and Improved Relaxations for Tensor Recovery ICML 2014 Standardized Mutual Information for Clustering Comparisons: One Step Further in Adjustment for Chance ICML 2014 Statistical Analysis of Metric Graph Reconstruction JMLR 2014 Using Projection Kurtosis Concentration Of Natural Images For Blind Noise Covariance Matrix Estimation CVPR 2014 A Competitive Test for Uniformity of Monotone Distributions AISTATS 2013 Adaptive Sparsity in Gaussian Graphical Models ICML 2013 A Kernel Test for Three-Variable Interactions NeurIPS 2013 Annealing between distributions by averaging moments NeurIPS 2013 A Parallel, Block Greedy Method for Sparse Inverse Covariance Estimation for Ultra-high Dimensions AISTATS 2013 A Risk Comparison of Ordinary Least Squares vs Ridge Regression JMLR 2013 A Statistical Model for Recreational Trails in Aerial Images CVPR 2013 Asymptotic Results on Adaptive False Discovery Rate Controlling Procedures Based on Kernel Estimators JMLR 2013 Blind Signal Separation in the Presence of Gaussian Noise COLT 2013 B-test: A Non-parametric, Low Variance Kernel Two-sample Test NeurIPS 2013 Characterizing the Representer Theorem ICML 2013 Confidence Intervals and Hypothesis Testing for High-Dimensional Statistical Models NeurIPS 2013 Consistency of Robust Kernel Density Estimators COLT 2013 Consistent Selection of Tuning Parameters via Variable Selection Stability JMLR 2013 Density estimation from unweighted k-nearest neighbor graphs: a roadmap NeurIPS 2013