sparse estimation

Positive Definite Sparse Covariance Estimation via Dual Space Optimization AAAI 2026 Sparse Topic Modeling via Spectral Decomposition and Thresholding JMLR 2026 Explainable Neural Networks with Guarantee: A Sparse Estimation Approach AAAI 2025 Outlier Robust and Sparse Estimation of Linear Regression Coefficients JMLR 2025 Estimation of Sparse Gaussian Graphical Models with Hidden Clustering Structure JMLR 2024 GmGM: a fast multi-axis Gaussian graphical model AISTATS 2024 Learning Macroscopic Dynamics from Partial Microscopic Observations NeurIPS 2024 On the Lasso for Graphical Continuous Lyapunov Models CLeaR 2024 Robust Sparse Estimation for Gaussians with Optimal Error under Huber Contamination ICML 2024 Exponential Generalization Bounds with Near-Optimal Rates for L_q-Stable Algorithms ICLR 2023 Sparse Markov Models for High-dimensional Inference JMLR 2023 Tilted Sparse Additive Models ICML 2023 A Completely Tuning-Free and Robust Approach to Sparse Precision Matrix Estimation ICML 2022 Denoising and change point localisation in piecewise-constant high-dimensional regression coefficients AISTATS 2022 EiGLasso for Scalable Sparse Kronecker-Sum Inverse Covariance Estimation JMLR 2022 Joint Estimation and Inference for Data Integration Problems based on Multiple Multi-layered Gaussian Graphical Models JMLR 2022 List-Decodable Sparse Mean Estimation NeurIPS 2022 List-Decodable Sparse Mean Estimation via Difference-of-Pairs Filtering NeurIPS 2022 Outlier-Robust Sparse Mean Estimation for Heavy-Tailed Distributions NeurIPS 2022 Robust Sparse Mean Estimation via Sum of Squares COLT 2022 The Role of Interactivity in Structured Estimation COLT 2022 Estimating Sparse Discrete Distributions Under Privacy and Communication Constraints ALT 2021 Minimax Estimation of Laplacian Constrained Precision Matrices AISTATS 2021 Scalable Inference of Sparsely-changing Gaussian Markov Random Fields NeurIPS 2021 Agnostic Estimation for Phase Retrieval JMLR 2020