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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

Inferring Change Points in High-Dimensional Regression via Approximate Message Passing JMLR 2025
Sketching in High-Dimensional Regression With Big Data Using Gaussian Scale Mixture Priors JMLR 2025
Linear Hypothesis Testing in High-Dimensional Expected Shortfall Regression with Heavy-Tailed Errors JMLR 2025
Optimal subsampling for high-dimensional partially linear models via machine learning methods JMLR 2025
Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers JMLR 2025
Reliever: Relieving the Burden of Costly Model Fits for Changepoint Detection JMLR 2025
Decentralized Sparse Linear Regression via Gradient-Tracking JMLR 2025
High-Dimensional L2-Boosting: Rate of Convergence JMLR 2025
Unified Transfer Learning in High-Dimensional Linear Regression AISTATS 2024
Computational-Statistical Gaps in Gaussian Single-Index Models (Extended Abstract) COLT 2024
Model Collapse Demystified: The Case of Regression NIPS 2024
Statistical analysis for a penalized EM algorithm in high-dimensional mixture linear regression model JMLR 2024
Inference on High-dimensional Single-index Models with Streaming Data JMLR 2024
Revisiting Differentially Private ReLU Regression NIPS 2024
The Non-Overlapping Statistical Approximation to Overlapping Group Lasso JMLR 2024
TransFusion: Covariate-Shift Robust Transfer Learning for High-Dimensional Regression AISTATS 2024
Logistic Regression Under Network Dependence JMLR 2024
A minimax optimal approach to high-dimensional double sparse linear regression JMLR 2024
On the Computational Complexity of Private High-dimensional Model Selection NIPS 2024
Federated Asymptotics: a model to compare federated learning algorithms AISTATS 2023
Sub-optimality of the Naive Mean Field approximation for proportional high-dimensional Linear Regression NIPS 2023
Confidence Intervals and Hypothesis Testing for High-dimensional Quantile Regression: Convolution Smoothing and Debiasing JMLR 2023
On Single-Index Models beyond Gaussian Data NIPS 2023
A Randomized Subspace-based Approach for Dimensionality Reduction and Important Variable Selection JMLR 2023
Modular Regression: Improving Linear Models by Incorporating Auxiliary Data JMLR 2023