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Coordinate descent optimization for <i>l</i><SUP>1</SUP> minimization with application to compressed sensing; a greedy algorithm
Author(s) -
Yingying Li,
Stanley Osher
Publication year - 2009
Publication title -
inverse problems and imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.755
H-Index - 40
eISSN - 1930-8345
pISSN - 1930-8337
DOI - 10.3934/ipi.2009.3.487
Subject(s) - compressed sensing , greedy algorithm , coordinate descent , minification , algorithm , basis (linear algebra) , basis pursuit , computer science , mathematical optimization , mathematics , matching pursuit , geometry
We propose a fast algorithm for solving the Basis Pursuit problem, min u $\{|u|_1\: \Au=f\}$, which has application to compressed sensing. We design an efficient method for solving the related unconstrained problem min u $E(u) = |u|_1 + \lambda \||Au-f\||^2_2$ based on a greedy coordinate descent method. We claim that in combination with a Bregman iterative method, our algorithm will achieve a solution with speed and accuracy competitive with some of the leading methods for the basis pursuit problem.

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