An efficient manifold regularized sparse non-negative matrix factorization model for large-scale recommender systems on GPUs-Reference-Cited by-同舟云学术

An efficient manifold regularized sparse non-negative matrix factorization model for large-scale recommender systems on GPUs

Published:2019-09 Issue: Volume:496 Page:464-484
ISSN:0020-0255
Container-title:Information Sciences
language:en
Short-container-title:Information Sciences

Author:

Li Hao^ORCID,Li Keqin^ORCID,An Jiyao^ORCID,Zheng Weihua,Li Kenli

Funder

National Natural Science Foundation of China

Natural Science Foundation of China

Natural Science Foundation of Hunan Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Computer Science Applications,Theoretical Computer Science,Control and Systems Engineering,Software

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4. Parallel space saving on multi-and many-core processors;Cafaro,2017

5. Graph regularized nonnegative matrix factorization for data representation;Cai;IEEE Trans. Pattern Anal. Mach. Intell.,2011

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