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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Veröffentlicht in:	Proceedings of the National Academy of Sciences - PNAS Jg. 106; H. 2; S. 369
Hauptverfasser:	Belabbas, Mohamed-Ali, Wolfe, Patrick J
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States 13.01.2009
Schlagworte:	Algorithms Artificial Intelligence Data Interpretation, Statistical Databases, Factual Information Storage and Retrieval - methods Methods Models, Statistical Software
ISSN:	1091-6490, 1091-6490
Online-Zugang:	Weitere Angaben
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