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Department of Mathematics,
Department of Mathematics,
University of California San Diego
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Math 296 - Graduate Colloquium
Ioana Dumitriu
UC San Diego
Random matrices, random graphs, and applications to machine learning
Abstract:
The last decade has seen tremendous progress in applying random matrix methods to adjacency matrices or Laplacians of random graphs, in order to understand their spectra and be able to apply the new results to algorithms in machine learning, coding theory, data science, etc. Nevertheless, many problems remain. I will present some of the most interesting tools and new results and mention some (still) open problems.
Host: Elham Izadi
January 26, 2021
3:00 PM
Contact Elham Izadi for Zoom link
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