Robustness in sparse linear models: relative efficiency based on robust
approximate message passing

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Robustness in sparse linear models: relative efficiency based on robust approximate message passing

31 July 2015

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Papers citing "Robustness in sparse linear models: relative efficiency based on robust approximate message passing"

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Title
Precise Error Analysis of Regularized M-estimators in High-dimensions Christos Thrampoulidis Ehsan Abbasi B. Hassibi 189 220 0 23 Jan 2016
Statistical consistency and asymptotic normality for high-dimensional robust M-estimators Po-Ling Loh 100 194 0 01 Jan 2015
High Dimensional Robust M-Estimation: Asymptotic Variance via Approximate Message Passing D. Donoho Andrea Montanari 218 221 0 28 Oct 2013
Adaptive robust variable selection Jianqing Fan Yingying Fan Emre Barut 576 200 0 22 May 2012
Robust computation of linear models by convex relaxation Gilad Lerman Michael B. McCoy J. Tropp Teng Zhang 147 161 0 18 Feb 2012
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers S. Negahban Pradeep Ravikumar Martin J. Wainwright Bin Yu 474 1,379 0 13 Oct 2010
The LASSO risk for gaussian matrices Mohsen Bayati Andrea Montanari 186 318 0 16 Aug 2010
The Noise-Sensitivity Phase Transition in Compressed Sensing D. Donoho A. Maleki Andrea Montanari 92 382 0 08 Apr 2010