Spectral methods in machine learning and new strategies for very large datasets

Spectral methods are of fundamental importance in statistics and machine learning, because they underlie algorithms from classical principal components analysis to more recent approaches that exploit manifold structure. In most cases, the core technical problem can be reduced to computing a low-rank...

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Bibliographic Details

Published in:	Proceedings of the National Academy of Sciences - PNAS Vol. 106; no. 2; p. 369
Main Authors:	Belabbas, Mohamed-Ali, Wolfe, Patrick J
Format:	Journal Article
Language:	English
Published:	United States 13.01.2009
Subjects:	Algorithms Artificial Intelligence Data Interpretation, Statistical Databases, Factual Information Storage and Retrieval - methods Methods Models, Statistical Software
ISSN:	1091-6490, 1091-6490
Online Access:	Get more information
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