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dc.contributor.authorBenhamou, Eric
dc.contributor.authorAtif, Jamal
dc.contributor.authorLaraki, Rida
dc.date.accessioned2019-05-14T10:25:16Z
dc.date.available2019-05-14T10:25:16Z
dc.date.issued2019-01
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/18906
dc.language.isoenen
dc.subjectsub-Gaussian tailed random matricesen
dc.subject.ddc515en
dc.titleA short note on the operator norm upper bound for sub-Gaussian tailed random matricesen
dc.typeDocument de travail / Working paper
dc.description.abstractenThis paper investigates an upper bound of the operator norm for sub-Gaussian tailed random matrices. A lot of attention has been put on uniformly bounded sub-Gaussian tailed random matrices with independent coefficients. However, little has been done for sub-Gaussian tailed random matrices whose matrix coefficients variance are not equal or for matrix for which coefficients are not independent. This is precisely the subject of this paper. After proving that random matrices with uniform sub-Gaussian tailed independent coefficients satisfy the Tracy Widom bound, that is,their matrix operator norm remains bounded by O(√n) with overwhelming probability, we prove that a less stringent condition is that the matrix rows are independent and uniformly sub-Gaussian. This does not impose in particular that all matrix coefficients are independent, but only their rows, which is a weaker condition.en
dc.publisher.namePreprint Lamsadeen
dc.publisher.cityParisen
dc.identifier.citationpages12en
dc.relation.ispartofseriestitlePreprint Lamsadeen
dc.identifier.urlsitehttps://arxiv.org/abs/1812.09618v2en
dc.subject.ddclabelAnalyseen
dc.identifier.citationdate2019
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.date.updated2019-04-30T12:03:44Z
hal.person.labIds989
hal.person.labIds989
hal.person.labIds989
hal.identifierhal-02128502*


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