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SIAMIS
2011
13 years 2 months ago
Gradient-Based Methods for Sparse Recovery
The convergence rate is analyzed for the sparse reconstruction by separable approximation (SpaRSA) algorithm for minimizing a sum f(x) + ψ(x), where f is smooth and ψ is convex, ...
William W. Hager, Dzung T. Phan, Hongchao Zhang
SIAMIS
2010
190views more  SIAMIS 2010»
13 years 2 months ago
Analysis and Generalizations of the Linearized Bregman Method
This paper analyzes and improves the linearized Bregman method for solving the basis pursuit and related sparse optimization problems. The analysis shows that the linearized Bregma...
Wotao Yin
CISS
2011
IEEE
12 years 11 months ago
Stable manifold embeddings with operators satisfying the Restricted Isometry Property
—Signals of interests can often be thought to come from a low dimensional signal model. The exploitation of this fact has led to many recent interesting advances in signal proces...
Han Lun Yap, Michael B. Wakin, Christopher J. Roze...
CISS
2011
IEEE
12 years 11 months ago
The Restricted Isometry Property for block diagonal matrices
—In compressive sensing (CS), the Restricted Isometry Property (RIP) is a powerful condition on measurement operators which ensures robust recovery of sparse vectors is possible ...
Han Lun Yap, Armin Eftekhari, Michael B. Wakin, Ch...
ICASSP
2011
IEEE
12 years 11 months ago
Recovery of sparse perturbations in Least Squares problems
We show that the exact recovery of sparse perturbations on the coefficient matrix in overdetermined Least Squares problems is possible for a large class of perturbation structure...
Mert Pilanci, Orhan Arikan