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Robust, Interpretable Statistical Models: Sparse Regression with the LASSO
Hussein Hazimeh - Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization
4 3 Sparse Regression | Machine Learning
Robust Sparse Covariance Estimation by Thresholding Tyler's M-estimator
High-Dimensional Sparse Cross-Modal Hashing with Fine-Grained Similarity Embedding
On the Power of Preconditioning in Sparse Linear Regression
Large-scale regression with sparse data
Sparse Regression LDPC Codes (arXiv:2311.07720)
On the Power of Preconditioning in Sparse Linear Regression
Some Problems of Robust High-dimensional Statistics
Robustness in High-Dimensional Inference Tasks
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Last Updated: September 28, 2026
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Constantine Caramanis (University of Texas at Austin) ... Po-Ling Loh (University of Wisconsin, Madison) ... CIRM VIRTUAL EVENT Recorded during the meeting "Mathematical Methods of Modern Statistics 2" the June 03, 2020 by the ... In recent years, there has been significant research into the problem of estimating covariance and precision matrices in ... Part of Discrete Optimization Talks: talks.discreteopt.com Hussein Hazimeh -- MIT Boaz Nadler (Weizmann Institute of Science) ... Authors: Yongxin Wang (Shandong University), Zhen-Duo Chen (Shandong University), Xin Luo (Shandong University) and Xin- ... Frederic Koehler (UC Berkeley) Meet the Fellows Welcome Event. This article introduces a novel concatenated coding scheme called Raghu Meka (UCLA) simons.berkeley.edu/talks/power-preconditioning- Gilad Lerman (University of Minnesota) simons.berkeley.edu/talks/some-problems- Jelena Bradic (UC San Diego) simons.berkeley.edu/talks/robustness-
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