Corrupted Sensing: Novel Guarantees for Separating Structured Signals

v1v2 (latest)

Corrupted Sensing: Novel Guarantees for Separating Structured Signals

11 May 2013

Lester W. Mackey

ArXiv (abs)PDF HTML

Papers citing "Corrupted Sensing: Novel Guarantees for Separating Structured Signals"

11 / 11 papers shown

Title
On Robust Recovery of Signals from Indirect Observations Yannis Bekri A. Juditsky A. Nemirovski 58 2 0 12 Sep 2023
Fast and Reliable Parameter Estimation from Nonlinear Observations Samet Oymak Mahdi Soltanolkotabi 194 25 0 23 Oct 2016
Precise Error Analysis of Regularized M-estimators in High-dimensions Christos Thrampoulidis Ehsan Abbasi B. Hassibi 194 222 0 23 Jan 2016
Signal Recovery on Incoherent Manifolds Chinmay Hegde Richard G. Baraniuk 62 44 0 08 Feb 2012
Compressed Sensing and Matrix Completion with Constant Proportion of Corruptions Xiaodong Li 122 180 0 06 Apr 2011
Exact recoverability from dense corrupted observations via $L_1$ minimization Nam H. Nguyen T. Tran 96 117 0 07 Feb 2011
The Convex Geometry of Linear Inverse Problems V. Chandrasekaran Benjamin Recht P. Parrilo A. Willsky 211 1,341 0 03 Dec 2010
A Unified Framework for High-Dimensional Analysis of M-Estimators with Decomposable Regularizers S. Negahban Pradeep Ravikumar Martin J. Wainwright Bin Yu 477 1,379 0 13 Oct 2010
A note on the group lasso and a sparse group lasso J. Friedman Trevor Hastie Robert Tibshirani 225 841 0 05 Jan 2010
Rank-Sparsity Incoherence for Matrix Decomposition V. Chandrasekaran Sujay Sanghavi P. Parrilo A. Willsky CML 257 1,111 0 11 Jun 2009
$On Recovery of Sparse Signals via $\ell_1$ Minimization$ On Recovery of Sparse Signals via $\ell_1$ Minimization T. Cai Guangwu Xu Jun Zhang 113 155 0 01 May 2008

We use cookies and other tracking technologies to improve your browsing experience on our website, to show you personalized content and targeted ads, to analyze our website traffic, and to understand where our visitors are coming from. See our policy.