high-dimensional statistics

Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time NeurIPS 2020 WONDER: Weighted One-shot Distributed Ridge Regression in High Dimensions JMLR 2020 A Kernel Random Matrix-Based Approach for Sparse PCA ICLR 2019 Doubly-Robust Lasso Bandit NeurIPS 2019 Faster Algorithms for High-Dimensional Robust Covariance Estimation COLT 2019 High-Dimensional Poisson Structural Equation Model Learning via ℓ_1-Regularized Regression JMLR 2019 High-dimensional Varying Index Coefficient Models via Stein's Identity JMLR 2019 Nonconvex sampling with the Metropolis-adjusted Langevin algorithm COLT 2019 Nonuniformity of P-values Can Occur Early in Diverging Dimensions JMLR 2019 On Mean Estimation for General Norms with Statistical Queries COLT 2019 On Robustness of Principal Component Regression NeurIPS 2019 Outlier-Robust High-Dimensional Sparse Estimation via Iterative Filtering NeurIPS 2019 Precision Matrix Estimation with Noisy and Missing Data AISTATS 2019 Principal Component Analysis in the Local Differential Privacy Model IJCAI 2019 Quantum Entropy Scoring for Fast Robust Mean Estimation and Improved Outlier Detection NeurIPS 2019 Statistical-Computational Tradeoff in Single Index Models NeurIPS 2019 The Impact of Regularization on High-dimensional Logistic Regression NeurIPS 2019 A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models ICML 2018 Algebraic tests of general Gaussian latent tree models NeurIPS 2018 An Improved Analysis of Alternating Minimization for Structured Multi-Response Regression NeurIPS 2018 Can We Trust the Bootstrap in High-dimensions? The Case of Linear Models JMLR 2018 Covariate Adjusted Precision Matrix Estimation via Nonconvex Optimization ICML 2018 Detection limits in the high-dimensional spiked rectangular model COLT 2018 Learning linear structural equation models in polynomial time and sample complexity AISTATS 2018 On Tight Bounds for the Lasso JMLR 2018