Sketching for Linear Algebra III: Randomized Hadamard, Kernel Methods
Machine Learning seminar by Ken Clarkson, IBM Almaden
Hosted by Simons Institute for the Theory of Computing
Recording
Abstract
Building on the preceding linear-algebra tutorials, this lecture presents two further approaches to matrix sketching: leverage-score sampling and the Subsampled Randomized Hadamard Transform. It examines how these methods produce effective compressed matrix representations for a variety of applications.
Topics
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