Stochastics & Statistics Seminar – David Donoho (Stanford)
February 12, 2016 | 11-12pm | 32-123

ABSTRACT: Principal components is a true workhorse of science and technology,
applied everywhere from radio frequency signal processing to financial econometrics,genomics, and social network analysis. In this talk, I will review some of these applications and then describe the challenge posed by modern ‘big data asymptotics’ where there are roughly as many dimensions as observations;this setting has seemed in the past full of mysteries.Over the last ten years random matrix theory has developed a hostof new tools that now can be deployed to meet this challenge;I will describe these new tools and show how I think we have recently crossed a threshold where some of the former mysteries are now cleared up. This is joint work with Matan Gavish (Hebrew Univ),Iain Johnstone and Edgar Dobriban (Stanford).

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