Linear Methods for Large Data
Speaker: Dean Foster, University of Pennsylvania
Location: Warren Weaver Hall 1302
Date: Monday, April 20, 2015, 3:45 p.m.
Using random matrix theory, we now have some very easy to understand and fast to use methods of computing low rank representations of matrices. I have been using these methods as a hammer to improve several statistical methods. I'll discuss several of these in this talk. First, I'll show how these ideas can be used to speed up regression. Then I'll turn to using them to construct new linear features motivated by CCA's.