Tensor Decompositions
Tensor Decompositions is a mathematical framework in numerical linear algebra that generalizes matrix factorization techniques to higher-order tensors by decomposing a tensor into a product of simpler, structured components to reveal latent multilinear relationships.
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2017–2026
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Learning the parts of objects by non-negative matrix factorization
Daniel D. Lee, H. Sebastian Seung · Nature · 1999 · 14.1K citations
Tensor Decompositions and Applications
Tamara G. Kolda, Brett W. Bader · SIAM Review · 2009 · 10.5K citations
Ivan Oseledets · SIAM Journal on Scientific Computing · 2011 · 2.6K citations
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University of Electronic Science and Technology of China, China
31 publications · 2.3K citations
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Centre National de la Recherche Scientifique
Paris, France
38 h-index
177 publications
10.5K citations

University of Electronic Science and Technology of China
Chengdu, China
38 h-index
246 publications
14.9K citations
KU Leuven
Leuven, Belgium
34 h-index
145 publications
13.1K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
32 h-index
71 publications
5.1K citations
Carnegie Mellon University
Pittsburgh, United States
29 h-index
76 publications
9K citations
RIKEN Center for Brain Science
Wako, Japan
27 h-index
81 publications
14.1K citations

Xi'an Jiaotong University
Xi'an, China
27 h-index
99 publications
9.3K citations

Chinese Academy of Sciences
Beijing, China
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78 publications
5.5K citations
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