A randomized algorithm for the decomposition of matrices

Given an m × n matrix A and a positive integer k, we describe a randomized procedure for the approximation of A with a matrix Z of rank k. The procedure relies on applying A T to a collection of l random vectors, where l is an integer equal to or slightly greater than k; the scheme is efficient when...

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Bibliographic Details
Published in:	Applied and computational harmonic analysis Vol. 30; no. 1; pp. 47 - 68
Main Authors:	Martinsson, Per-Gunnar, Rokhlin, Vladimir, Tygert, Mark
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 2011
Subjects:	Algorithm Algorithms Approximation Decomposition Estimates Integers Lanczos Low rank Mathematical analysis Matrix Randomized SVD Vectors (mathematics) SVD Lanczos Randomized Matrix Algorithm Low rank
ISSN:	1063-5203, 1096-603X
Online Access:	Get full text
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