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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Vydáno v:	Applied numerical mathematics Ročník 164; s. 101 - 124
Hlavní autoři:	Wu, Gang, Li, Fei
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.06.2021
Témata:	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
On-line přístup:	Získat plný text
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