Computing non-negative tensor factorizations

Optimization Methods and Software

Volumn 23, Issue 4, 2008, Pages 631-647

  Friedlander, Michael P ^a   Hatz, Kathrin ^b  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

Alternating least squares; Block Gauss Seidel; N dimensional arrays; Non negative least squares; Non negative tensor factorization; Regularization; Sparse solutions; Tensors

Indexed keywords

ALGEBRA; ARTIFICIAL INTELLIGENCE; BLIND SOURCE SEPARATION; COMPUTER SOFTWARE; DATA STRUCTURES; DECISION SUPPORT SYSTEMS; INFORMATION MANAGEMENT; KNOWLEDGE MANAGEMENT; LEARNING SYSTEMS; LINEAR ALGEBRA; MATHEMATICAL PROGRAMMING; MATLAB; MATRIX ALGEBRA; SEARCH ENGINES; SOFTWARE PACKAGES; TENSORS;

DATA SETS; DATA-SETS; HIGH-DIMENSIONAL DATA; LATENT STRUCTURES; LOW RANK APPROXIMATIONS; MACHINE-LEARNING; MATLAB SOFTWARE PACKAGE; NON-NEGATIVE MATRIX FACTORIZATION (DNMF); TENSOR FACTORIZATION;

FACTORIZATION;

EID: 47249112550     PISSN: 10556788     EISSN: 10294937     Source Type: Journal    
DOI: 10.1080/10556780801996244     Document Type: Article

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