high-dimensional regression

Non-Convex Projected Gradient Descent for Generalized Low-Rank Tensor Regression JMLR 2019 On Robustness of Principal Component Regression NeurIPS 2019 Sparse High-Dimensional Isotonic Regression NeurIPS 2019 The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions ICML 2019 A Constructive Approach to L_0 Penalized Regression JMLR 2018 Approximate Leave-One-Out for Fast Parameter Tuning in High Dimensions ICML 2018 Can We Trust the Bootstrap in High-dimensions? The Case of Linear Models JMLR 2018 High Dimensional Linear Regression using Lattice Basis Reduction NeurIPS 2018 Sparse Concordance-assisted Learning for Optimal Treatment Decision JMLR 2018 Sparse Linear Isotonic Models AISTATS 2018 The xyz algorithm for fast interaction search in high-dimensional data JMLR 2018 Variable Selection via Penalized Neural Network: a Drop-Out-One Loss Approach ICML 2018 Alternating Estimation for Structured High-Dimensional Multi-Response Models NeurIPS 2017 Breaking the Curse of Dimensionality with Convex Neural Networks JMLR 2017 Collect at Once, Use Effectively: Making Non-interactive Locally Private Learning Possible ICML 2017 Communication-efficient Sparse Regression JMLR 2017 Gap Safe Screening Rules for Sparsity Enforcing Penalties JMLR 2017 Group Additive Structure Identification for Kernel Nonparametric Regression NeurIPS 2017 High-dimensional Non-Gaussian Single Index Models via Thresholded Score Function Estimation ICML 2017 Identifying a Minimal Class of Models for High--dimensional Data JMLR 2017 Learning ReLUs via Gradient Descent NeurIPS 2017 Localized Lasso for High-Dimensional Regression AISTATS 2017 Regularized Estimation and Testing for High-Dimensional Multi-Block Vector-Autoregressive Models JMLR 2017 Robust Structured Estimation with Single-Index Models ICML 2017 Sharp Oracle Inequalities for Square Root Regularization JMLR 2017