Tata Institute of Fundamental Research
Fast Low Rank Approximation via Random Projections
Student Seminar
Speaker:
Gugan Thoppe
Organiser:
Karthyek Rajhaa A M
Date:
Friday, 19 Apr 2013, 14:30 to 16:00
Venue:
A-212 (STCS Seminar Room)
(Scan to add to calendar)
Abstract:
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.
| Speaker: | Gugan Thoppe |
| Organiser: | Karthyek Rajhaa A M |
| Date: | Friday, 19 Apr 2013, 14:30 to 16:00 |
| Venue: | A-212 (STCS Seminar Room) |
(Scan to add to calendar)
Abstract:
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.