high-dimensional regression

Variational Inference in high-dimensional linear regression JMLR 2022 A Precise Performance Analysis of Support Vector Regression ICML 2021 Asymptotic Normality and Confidence Intervals for Prediction Risk of the Min-Norm Least Squares Estimator ICML 2021 A theory of high dimensional regression with arbitrary correlations between input features and target functions: sample complexity, multiple descent curves and a hierarchy of phase transitions ICML 2021 For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets NeurIPS 2021 Homogeneity Structure Learning in Large-scale Panel Data with Heavy-tailed Errors JMLR 2021 How rotational invariance of common kernels prevents generalization in high dimensions ICML 2021 Inference In High-dimensional Single-Index Models Under Symmetric Designs JMLR 2021 Integrative High Dimensional Multiple Testing with Heterogeneity under Data Sharing Constraints JMLR 2021 Localizing Changes in High-Dimensional Regression Models AISTATS 2021 Method of Contraction-Expansion (MOCE) for Simultaneous Inference in Linear Models JMLR 2021 On Empirical Risk Minimization with Dependent and Heavy-Tailed Data NeurIPS 2021 Optimal Minimax Variable Selection for Large-Scale Matrix Linear Regression Model JMLR 2021 Predictive Complexity Priors AISTATS 2021 Robust Inference for High-Dimensional Linear Models via Residual Randomization ICML 2021 Statistically and Computationally Efficient Change Point Localization in Regression Settings JMLR 2021 T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs NeurIPS 2021 A convex optimization formulation for multivariate regression NeurIPS 2020 Adaptive Reduced Rank Regression NeurIPS 2020 An Asymptotic Rate for the LASSO Loss AISTATS 2020 A Sparse Semismooth Newton Based Proximal Majorization-Minimization Algorithm for Nonconvex Square-Root-Loss Regression Problems JMLR 2020 Distributed High-dimensional Regression Under a Quantile Loss Function JMLR 2020 Doubly Distributed Supervised Learning and Inference with High-Dimensional Correlated Outcomes JMLR 2020 Empirical Priors for Prediction in Sparse High-dimensional Linear Regression JMLR 2020 Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions AISTATS 2020