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» A First-Order Smoothed Penalty Method for Compressed Sensing
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SIAMIS
2011
12 years 11 months ago
NESTA: A Fast and Accurate First-Order Method for Sparse Recovery
Abstract. Accurate signal recovery or image reconstruction from indirect and possibly undersampled data is a topic of considerable interest; for example, the literature in the rece...
Stephen Becker, Jérôme Bobin, Emmanue...
CISS
2011
IEEE
12 years 8 months ago
Sparsity penalties in dynamical system estimation
—In this work we address the problem of state estimation in dynamical systems using recent developments in compressive sensing and sparse approximation. We formulate the traditio...
Adam Charles, Muhammad Salman Asif, Justin K. Romb...
CORR
2011
Springer
214views Education» more  CORR 2011»
12 years 8 months ago
Convex Approaches to Model Wavelet Sparsity Patterns
Statistical dependencies among wavelet coefficients are commonly represented by graphical models such as hidden Markov trees (HMTs). However, in linear inverse problems such as d...
Nikhil S. Rao, Robert D. Nowak, Stephen J. Wright,...
SIAMIS
2010
190views more  SIAMIS 2010»
12 years 11 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