Communication avoiding low rank matrix approximation, an unified perspective on deterministic and randomized approaches

Abstract: In this talk we present an unified perspective on deterministic and randomized approaches for computing the low rank approximation of a matrix. We survey recent approaches that allow to minimize communication and discuss a generalized LU factorization that allows to unify several existing algorithms. For this factorization we present an improved analysis which combines deterministic guarantees with sketching ensembles satisfying Johnson-Lindenstrauss properties. We then extend some of the algorithms to computing the low rank approximation of a tensor by using HOSVD while also avoiding communication.

numerical analysis

Audience: researchers in the topic

E-NLA - Online seminar series on numerical linear algebra

Series comments: E-NLA is an online seminar series dedicated to topics in Numerical Linear Algebra. Talks take place on Wednesdays at 4pm (Central European Time) via Zoom and are initially scheduled on a weekly basis.

To join the seminar, please complete the sign up form at the bottom of the webpage. Information about how to connect to the conference call will be circulated via email to all registered attendees.