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high-dimensional regression

142 papers

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Co-occurring keywords

sparse regression (175) feature selection (649) variable selection (146) linear regression (282) high-dimensional statistics (145) sparse optimization (246) high-dimensional datum (158) distributed learning (563) convex optimization (1321) model selection (456)

Papers

Optimal Minimax Variable Selection for Large-Scale Matrix Linear Regression Model JMLR 2021
A Precise Performance Analysis of Support Vector Regression ICML 2021
Robust Inference for High-Dimensional Linear Models via Residual Randomization ICML 2021
How rotational invariance of common kernels prevents generalization in high dimensions ICML 2021
Asymptotic Normality and Confidence Intervals for Prediction Risk of the Min-Norm Least Squares Estimator ICML 2021
On Empirical Risk Minimization with Dependent and Heavy-Tailed Data NIPS 2021
T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs NIPS 2021
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets NIPS 2021
High-Dimensional Sparse Linear Bandits NIPS 2020
High-Dimensional Interactions Detection with Sparse Principal Hessian Matrix JMLR 2020
Scalable Approximate MCMC Algorithms for the Horseshoe Prior JMLR 2020
Prediction regions through Inverse Regression JMLR 2020
Empirical Priors for Prediction in Sparse High-dimensional Linear Regression JMLR 2020
A Sparse Semismooth Newton Based Proximal Majorization-Minimization Algorithm for Nonconvex Square-Root-Loss Regression Problems JMLR 2020
Spectral Deconfounding via Perturbed Sparse Linear Models JMLR 2020
Rank-based Lasso - efficient methods for high-dimensional robust model selection JMLR 2020
Generalisation error in learning with random features and the hidden manifold model ICML 2020
An Asymptotic Rate for the LASSO Loss AISTATS 2020
Error bounds in estimating the out-of-sample prediction error using leave-one-out cross validation in high-dimensions AISTATS 2020
Doubly Distributed Supervised Learning and Inference with High-Dimensional Correlated Outcomes JMLR 2020
WONDER: Weighted One-shot Distributed Ridge Regression in High Dimensions JMLR 2020
Adaptive Reduced Rank Regression NIPS 2020
Randomized tests for high-dimensional regression: A more efficient and powerful solution NIPS 2020
Multi-task Additive Models for Robust Estimation and Automatic Structure Discovery NIPS 2020
Transfer Learning via $\ell_1$ Regularization NIPS 2020