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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Veröffentlicht in:	Algorithmica Jg. 72; H. 1; S. 264 - 281
Hauptverfasser:	Witten, Rafi, Candès, Emmanuel
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Boston Springer US 01.05.2015
Schlagworte:	Algorithm Analysis and Problem Complexity Algorithms Computer Science Computer Systems Organization and Communication Networks Data Structures and Information Theory Mathematics of Computing Theory of Computation Matrix approximation Dimension reduction Random matrix Randomized linear algebra Pass efficient algorithm
ISSN:	0178-4617, 1432-0541
Online-Zugang:	Volltext
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