A randomized exponential canonical correlation analysis method for data analysis and dimensionality reduction

Canonical correlation analysis (CCA) is a famous data analysis method that has been successfully used in many areas. CCA extracts meaningful information from a pair of data sets, by seeking pairs of linear combinations from two sets of variables with maximum correlation. Mathematically, CCA resorts...

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Veröffentlicht in:	Applied numerical mathematics Jg. 164; S. 101 - 124
Hauptverfasser:	Wu, Gang, Li, Fei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.06.2021
Schlagworte:	Canonical correlation analysis (CCA) Exponential canonical correlation analysis (ECCA) Generalized eigenvalue problem Matrix exponential Randomized singular value decomposition (RSVD) Generalized eigenvalue problem Exponential canonical correlation analysis (ECCA) Randomized singular value decomposition (RSVD) Canonical correlation analysis (CCA) Matrix exponential
ISSN:	0168-9274, 1873-5460
Online-Zugang:	Volltext
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