Iteratively re-weighted least squares minimization for sparse recovery

Details Iteratively re-weighted least squares minimization for sparse recovery Iteratively re-weighted least squares minimization for sparse recovery

2008-07-03

arxiv.org/abs/0807.0575v1

Mathematics

Numerical Analysis

35 pages, 4 figures

Scientific paper

We analyze an Iteratively Re-weighted Least Squares (IRLS) algorithm for
promoting l1-minimization in sparse and compressible vector recovery. We prove
its convergence and we estimate its local rate. We show how the algorithm can
be modified in order to promote lt-minimization for t<1, and how this
modification produces superlinear rates of convergence.

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