A randomized generalized low rank approximations of matrices algorithm for high dimensionality reduction and image compression

Summary High‐dimensionality reduction techniques are very important tools in machine learning and data mining. The method of generalized low rank approximations of matrices (GLRAM) is a popular technique for dimensionality reduction and image compression. However, it suffers from heavily computation...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Numerical linear algebra with applications Jg. 28; H. 1
Hauptverfasser:	Li, Ke, Wu, Gang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Oxford Wiley Subscription Services, Inc 01.01.2021
Schlagworte:	Algorithms Data mining generalized low rank approximations of matrices high dimensionality reduction Image compression Machine learning randomized singular value decomposition Reconstruction Singular value decomposition
ISSN:	1070-5325, 1099-1506
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!