School of Technology and Computer Science Seminars

Fast Low Rank Approximation via Random Projections

by Mr. Gugan Thoppe (School of Technology and Computer Science, TIFR)

Friday, April 19, 2013 from to (Asia/Kolkata)
at Colaba Campus ( A-212 (STCS Seminar Room) )
Description
Given an m x n matrix A, we define the rank-k approximation of A as a matrix B of same size and of rank at most k such that A and B are close in the Frobenius norm. In this talk, we will first give a geometric interpretation of this problem and relate it to the singular value of decomposition (SVD) of the matrix A. We will then use this knowledge to understand why a fast low rank approximation algorithm is to be expected. If time permits, we will see some applications of low rank approximations to a class of fixed point and minimization problems.