sparse regression

Adaptive Forward Stepwise: A Method for High Sparsity Regression JMLR 2026 A Debiased LASSO Estimator for Design Matrices with Non-zero Mean Elements UAI 2026 Differentiable Sparse Identification of Lagrangian Dynamics AAAI 2026 Best Subset Selection: Optimal Pursuit for Feature Selection and Elimination ICML 2025 Effects of Momentum in Implicit Bias of Gradient Flow for Diagonal Linear Networks AAAI 2025 Rank-one Convexification for Sparse Regression JMLR 2025 A minimax optimal approach to high-dimensional double sparse linear regression JMLR 2024 Consistency of Dictionary-Based Manifold Learning AISTATS 2024 Fast, blind, and accurate: Tuning-free sparse regression with global linear convergence COLT 2024 Fast Iterative Hard Thresholding Methods with Pruning Gradient Computations NeurIPS 2024 High-dimensional (Group) Adversarial Training in Linear Regression NeurIPS 2024 Implicit Regularization of Decentralized Gradient Descent for Sparse Regression NeurIPS 2024 Learning Macroscopic Dynamics from Partial Microscopic Observations NeurIPS 2024 On the Computational Complexity of Private High-dimensional Model Selection NeurIPS 2024 Robust Sparse Regression with Non-Isotropic Designs NeurIPS 2024 Solving Sparse \& High-Dimensional-Output Regression via Compression NeurIPS 2024 Symmetry-Informed Governing Equation Discovery NeurIPS 2024 The Reliability of OKRidge Method in Solving Sparse Ridge Regression Problems NeurIPS 2024 The Solution Path of SLOPE AISTATS 2024 Truthful High Dimensional Sparse Linear Regression NeurIPS 2024 Vision-based Discovery of Nonlinear Dynamics for 3D Moving Target IJCAI 2024 Average case analysis of Lasso under ultra sparse conditions AISTATS 2023 Conditional Matrix Flows for Gaussian Graphical Models NeurIPS 2023 Coordinate Descent for SLOPE AISTATS 2023 Distributed Sparse Regression via Penalization JMLR 2023