An algorithm for low-rank matrix factorization and its applications

This paper proposes a valid and fast algorithm for low-rank matrix factorization. There are multiple applications for low-rank matrix factorization, and numerous algorithms have been developed to solve this problem. However, many algorithms do not use rank directly; instead, they minimize a nuclear...

Celý popis

Podrobná bibliografia

Vydané v:	Neurocomputing (Amsterdam) Ročník 275; s. 1012 - 1020
Hlavní autori:	Chen, Baiyu, Yang, Zi, Yang, Zhouwang
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier B.V 31.01.2018
Predmet:	Augmented Lagrangian method Low-rank representation Matrix factorization Sparseness Augmented Lagrangian method Matrix factorization Low-rank representation Sparseness
ISSN:	0925-2312, 1872-8286
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!