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An upper bound on the smallest singular value of a square random matrix Tatarko, Kateryna Mar 27, 2018

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Title An upper bound on the smallest singular value of a square random matrix
Creator Tatarko, Kateryna
Publisher Banff International Research Station for Mathematical Innovation and Discovery
Date Issued 2018-03-27T14:33
Description Let $A = (a_{ij})$ be a square $n\times n$ matrix with i.i.d. zero mean and unit variance entries. In a paper by Rudelson and Vershynin it was shown that the upper bound for a smallest singular value $s_n(A)$ is of order $n^{-\frac12}$ with probability close to one under additional assumption on entries of $A$ that $\mathbb{E}a^4_{ij} < \infty$. We remove the assumption on the fourth moment and show the upper bound assuming only $\mathbb{E}a^2_{ij} = 1.$
Extent 26 minutes
Subject Mathematics
Functional analysis
Convex and discrete geometry
Geographic Location Banff (Alta.)
Type Moving Image
FileFormat video/mp4
Language eng
Notes Author affiliation: University of Alberta
Series BIRS Workshop Lecture Videos (Banff, Alta)
Date Available 2018-09-24
Provider Vancouver : University of British Columbia Library
Rights Attribution-NonCommercial-NoDerivatives 4.0 International
DOI 10.14288/1.0372142
URI http://hdl.handle.net/2429/67237
Affiliation Non UBC
Peer Review Status Unreviewed
Scholarly Level Graduate
Rights URI http://creativecommons.org/licenses/by-nc-nd/4.0/
AggregatedSourceRepository DSpace

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48630-201803271433-Tatarko_lrv.mp4 [ 118.17MB ]
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48630-1.0372142.ris

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