On Low Rank Matrix Approximations with Applications to Synthesis Problem in Compressed Sensing

DOI10.1137/100792251zbMath1231.90404arXiv1001.5103OpenAlexW2763109466WikidataQ57392896 ScholiaQ57392896MaRDI QIDQ3112405

Fatma Kılınç-Karzan, Arkadi Nemirovski, Anatoli B. Juditsky

Publication date: 16 January 2012

Published in: SIAM Journal on Matrix Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1001.5103

zbMATH Keywords

randomized algorithmscompressed sensinglow rank approximation of matrices\(\ell_1\)-recovery

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Approximation methods and heuristics in mathematical programming (90C59) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Approximation algorithms (68W25) Vector spaces, linear dependence, rank, lineability (15A03)

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Low-rank matrix approximation in the infinity norm ⋮ Accuracy guaranties for \(\ell_{1}\) recovery of block-sparse signals

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