Uniform Uncertainty Principle for Bernoulli and Subgaussian Ensembles

dc.contributor.authorMendelson, Shahar
dc.contributor.authorPajor, Alain
dc.contributor.authorTomczak-Jaegermann, Nicole
dc.date.accessioned2015-12-08T22:18:10Z
dc.date.issued2008
dc.date.updated2016-02-24T10:35:15Z
dc.description.abstractThe paper considers random matrices with independent subgaussian columns and provides a new elementary proof of the Uniform Uncertainty Principle for such matrices. The Principle was introduced by Candes, Romberg and Tao in 2004; for subgaussian random matrices it was carlier proved by the present authors, as a consequence of a general result based on a generic chaining method of Talagrand. The present proof combines a simple measure concentration and a covering argument, which are standard tools of high-dimensional convexity.
dc.identifier.issn0176-4276
dc.identifier.urihttp://hdl.handle.net/1885/31228
dc.publisherSpringer
dc.sourceConstructive Approximation
dc.subjectKeywords: Approximate reconstruction; Generic chaining; Random matrices; Uniform uncertainty principle
dc.titleUniform Uncertainty Principle for Bernoulli and Subgaussian Ensembles
dc.typeJournal article
local.bibliographicCitation.issue3
local.bibliographicCitation.lastpage289
local.bibliographicCitation.startpage277
local.contributor.affiliationMendelson, Shahar, College of Physical and Mathematical Sciences, ANU
local.contributor.affiliationPajor, Alain, Universite de Marne-la-Vallee
local.contributor.affiliationTomczak-Jaegermann, Nicole, University of Alberta
local.contributor.authoremailu4011413@anu.edu.au
local.contributor.authoruidMendelson, Shahar, u4011413
local.description.embargo2037-12-31
local.description.notesImported from ARIES
local.identifier.absfor010405 - Statistical Theory
local.identifier.ariespublicationu4085724xPUB81
local.identifier.citationvolume28
local.identifier.doi10.1007/s00365-007-9005-8
local.identifier.scopusID2-s2.0-55649100730
local.identifier.uidSubmittedByu4085724
local.type.statusPublished Version

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