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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Vydané v:	Proceedings of the National Academy of Sciences - PNAS Ročník 106; číslo 2; s. 369
Hlavní autori:	Belabbas, Mohamed-Ali, Wolfe, Patrick J
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 13.01.2009
Predmet:	Algorithms Artificial Intelligence Data Interpretation, Statistical Databases, Factual Information Storage and Retrieval - methods Methods Models, Statistical Software
ISSN:	1091-6490, 1091-6490
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