How to reduce dimension with PCA and random projections?

Yang, Fan; Liu, Sifan; Dobriban, Edgar; Woodruff, David P

Yang, Fan; Liu, Sifan; Dobriban, Edgar; Woodruff, David P.

Afiliación

Yang F; Wharton Statistics Department, University of Pennsylvania, Philadelphia, PA 19104, USA.
Liu S; Department of Statistics, Stanford University, Stanford, CA 94305, USA.
Dobriban E; Wharton Statistics Department, University of Pennsylvania, Philadelphia, PA 19104, USA.
Woodruff DP; Department of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.

IEEE Trans Inf Theory ; 67(12): 8154-8189, 2021 Dec.

Article en En | MEDLINE | ID: mdl-35695837

Palabras clave

Dimension reduction; principal component analysis; random matrix theory; random projection; sketching

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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Clinical_trials Idioma: En Revista: IEEE Trans Inf Theory Año: 2021 Tipo del documento: Article País de afiliación: Estados Unidos

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