15482

Video URL

https://simons.berkeley.edu/talks/tbd-135

Randomized Algorithms in Linear Algebra

(2020). Randomized Algorithms in Linear Algebra. The Simons Institute for the Theory of Computing. https://simons.berkeley.edu/talks/tbd-135

Randomized Algorithms in Linear Algebra. The Simons Institute for the Theory of Computing, Feb. 25, 2020, https://simons.berkeley.edu/talks/tbd-135 

          @misc{ scivideos_15482,
            doi = {},
            url = {https://simons.berkeley.edu/talks/tbd-135},
            author = {},
            keywords = {},
            language = {en},
            title = {Randomized Algorithms in Linear Algebra},
            publisher = {The Simons Institute for the Theory of Computing},
            year = {2020},
            month = {feb},
            note = {15482 see, \url{https://scivideos.org/index.php/Simons-Institute/15482}}
          }
Ravi Kannan (Microsoft Research India)
Talk number15482
Source RepositorySimons Institute
Subject

Abstract

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.