Randomized Algorithms for Low-Rank Matrix Factorizations: Sharp Performance Bounds

The development of randomized algorithms for numerical linear algebra, e.g. for computing approximate QR and SVD factorizations, has recently become an intense area of research. This paper studies one of the most frequently discussed algorithms in the literature for dimensionality reduction—specific...

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Bibliographic Details
Published in:Algorithmica Vol. 72; no. 1; pp. 264 - 281
Main Authors: Witten, Rafi, Candès, Emmanuel
Format: Journal Article
Language:English
Published: Boston Springer US 01.05.2015
Subjects:
ISSN:0178-4617, 1432-0541
Online Access:Get full text
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