Title
A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation
Abstract
We propose a fast algorithm for solving the $\ell_1$-regularized minimization problem $\min_{x\in\mathbb{R}^n}\mu\|x\|_1+\|Ax-b\|^2_2$ for recovering sparse solutions to an undetermined system of linear equations $Ax=b$. The algorithm is divided into two stages that are performed repeatedly. In the first stage a first-order iterative “shrinkage” method yields an estimate of the subset of components of $x$ likely to be nonzero in an optimal solution. Restricting the decision variables $x$ to this subset and fixing their signs at their current values reduces the $\ell_1$-norm $\|x\|_1$ to a linear function of $x$. The resulting subspace problem, which involves the minimization of a smaller and smooth quadratic function, is solved in the second phase. Our code FPC_AS embeds this basic two-stage algorithm in a continuation (homotopy) approach by assigning a decreasing sequence of values to $\mu$. This code exhibits state-of-the-art performance in terms of both its speed and its ability to recover sparse signals.
Year
DOI
Venue
2010
10.1137/090747695
SIAM J. Scientific Computing
Keywords
Field
DocType
linear function,sparse signal,sparse solution,basis pursuit,linear equation,shrinkage,sparse reconstruction,continuation,active set,smooth quadratic function,compressive sensing,subspace optimization,subspace problem,basic two-stage algorithm,regularized minimization problem,fast algorithm,code fpc_as,ℓ1-minimization,linear equations,first order,compressed sensing,iteration method
Mathematical analysis,Basis pursuit,Minification,Homotopy,Compressed sensing,Discrete mathematics,Combinatorics,Mathematical optimization,System of linear equations,Subspace topology,Algorithm,Quadratic function,Linear function,Mathematics
Journal
Volume
Issue
ISSN
32
4
1064-8275
Citations 
PageRank 
References 
47
3.10
31
Authors
4
Name
Order
Citations
PageRank
Zaiwen Wen193440.20
Wotao Yin25038243.92
Donald Goldfarb375563.99
Yin Zhang43492281.04