Generalized low-rank approximations of matrices revisited

IEEE Transactions on Neural Networks

Volumn 21, Issue 4, 2010, Pages 621-632

  Liu, Jun ^a   Chen, Songcan ^b   Zhou, Zhi Hua ^c   Tan, Xiaoyang ^b  

^a Arizona State University   (United States)

^b NANJING UNIVERSITY OF AERONAUTICS AND ASTRONAUTICS   (China)

^c NANJING UNIVERSITY   (China)

Author keywords

Dimensionality reduction; Generalized low rank approximations of matrices (GLRAM); Reconstruction error; Singular value decomposition (SVD)

Indexed keywords

BASIC PROPERTIES; CLASSIFICATION PERFORMANCE; COMPRESSION RATIOS; COMPUTATION TIME; DIMENSIONALITY REDUCTION; FUNDAMENTAL PROBLEM; LOW-RANK APPROXIMATIONS OF MATRICES; LOWER BOUNDS; MACHINE-LEARNING; OBJECTIVE FUNCTIONS; OPEN PROBLEMS; RECONSTRUCTION ERROR;

COMPRESSION RATIO (MACHINERY); IMAGE COMPRESSION; REPAIR;

SINGULAR VALUE DECOMPOSITION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; HUMAN; INFORMATION PROCESSING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATA COMPRESSION; HUMANS; PATTERN RECOGNITION, AUTOMATED;

EID: 77950866016     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2010.2040290     Document Type: Article

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