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arXiv:1501.01571 [math.PR]AbstractReferencesReviewsResources

An Introduction to Matrix Concentration Inequalities

Joel A. Tropp

Published 2015-01-07Version 1

In recent years, random matrices have come to play a major role in computational mathematics, but most of the classical areas of random matrix theory remain the province of experts. Over the last decade, with the advent of matrix concentration inequalities, research has advanced to the point where we can conquer many (formerly) challenging problems with a page or two of arithmetic. The aim of this monograph is to describe the most successful methods from this area along with some interesting examples that these techniques can illuminate.

Comments: 163 pages. To appear in Foundations and Trends in Machine Learning
Subjects: 60B20, 60F10, 60G50, 60G42
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