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A sparse Kaczmarz solver and a linearized Bregman method for online compressed sensing

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arxiv 1403.7543 v1 pith:345YRZ65 submitted 2014-03-28 math.OC cs.CVcs.ITcs.NAmath.ITmath.NA

A sparse Kaczmarz solver and a linearized Bregman method for online compressed sensing

Dirk A. Lorenz , Stephan Wenger , Frank Sch\"opfer , Marcus Magnor This is my paper
classification math.OC cs.CVcs.ITcs.NAmath.ITmath.NA
keywords frameworkkaczmarzmethodsparsealgorithmicbregmancompressedlinear
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An algorithmic framework to compute sparse or minimal-TV solutions of linear systems is proposed. The framework includes both the Kaczmarz method and the linearized Bregman method as special cases and also several new methods such as a sparse Kaczmarz solver. The algorithmic framework has a variety of applications and is especially useful for problems in which the linear measurements are slow and expensive to obtain. We present examples for online compressed sensing, TV tomographic reconstruction and radio interferometry.

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