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Applied random matrix theory

Mathematics of Data & Decisions

Speaker: Joel Tropp, Caltech
Related Webpage: http://maddd.math.ucdavis.edu
Location: 1147 MSB
Start time: Mon, Oct 1 2018, 4:30PM

Random matrices now play a role in many areas of theoretical, applied, and computational mathematics. Therefore, it is desirable to have tools for studying random matrices that are flexible, easy to use, and powerful. Over the last fifteen years, researchers have developed a remarkable family of results, called matrix concentration inequalities, that balance these criteria. This talk offers an invitation to the field of matrix concentration inequalities and their applications.