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Sparse Recovery with Linear and Nonlinear Observations: Dependent and
  Noisy Data

Sparse Recovery with Linear and Nonlinear Observations: Dependent and Noisy Data

12 March 2014
Cem Aksoylar
Venkatesh Saligrama
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Papers citing "Sparse Recovery with Linear and Nonlinear Observations: Dependent and Noisy Data"

6 / 6 papers shown
Title
Sparse Signal Processing with Linear and Nonlinear Observations: A
  Unified Shannon-Theoretic Approach
Sparse Signal Processing with Linear and Nonlinear Observations: A Unified Shannon-Theoretic Approach
Cem Aksoylar
George Atia
Venkatesh Saligrama
41
58
0
02 Apr 2013
Robust 1-bit compressed sensing and sparse logistic regression: A convex
  programming approach
Robust 1-bit compressed sensing and sparse logistic regression: A convex programming approach
Y. Plan
Roman Vershynin
180
457
0
06 Feb 2012
Optimal Phase Transitions in Compressed Sensing
Optimal Phase Transitions in Compressed Sensing
Yihong Wu
S. Verdú
58
149
0
29 Nov 2011
High-dimensional regression with noisy and missing data: Provable
  guarantees with nonconvexity
High-dimensional regression with noisy and missing data: Provable guarantees with nonconvexity
Po-Ling Loh
Martin J. Wainwright
103
560
0
16 Sep 2011
Near-ideal model selection by $\ell_1$ minimization
Near-ideal model selection by ℓ1\ell_1ℓ1​ minimization
Emmanuel J. Candès
Y. Plan
253
214
0
02 Jan 2008
Enhancing Sparsity by Reweighted L1 Minimization
Enhancing Sparsity by Reweighted L1 Minimization
Emmanuel J. Candes
M. Wakin
Stephen P. Boyd
172
5,027
0
10 Nov 2007
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