Spring 2020

Randomized Algorithms in Linear Algebra

Tuesday, Feb. 25, 2020 10:45 am11:15 am PST

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Ravi Kannan (Microsoft Research India)


Calvin Lab Auditorium

A small random sample of rows/columns of any matrix is a decent proxy for the matrix, provided sampling probabilities are proportional to squared lengths. Since the early theorems on this from the 90’s, there has been a substantial body of work using sampling (random projections and probabil-ties based on leverage scores are two examples) to reduce matrix sizes for Linear Algebra computations. The talk will describe theorems, applications and challenges in the area.

PDF icon Ravi Kannan Slides452.83 KB