Sparse alignment for robust tensor learning

IEEE Transactions on Neural Networks and Learning Systems

Volumn 25, Issue 10, 2014, Pages 1779-1792

  Lai, Zhihui ^a,b   Wong, Wai Keung ^c,d   Xu, Yong ^a   Zhao, Cairong ^e   Sun, Mingming ^f  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b SHENZHEN UNIVERSITY   (China)

^c HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

^d Shenzhen Institute of Polytechnics   (China)

^e TONGJI UNIVERSITY   (China)

^f NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Feature extraction; local alignment; manifold learning; sparse representation; tensor learning

Indexed keywords

ENCODING (SYMBOLS); EXTRACTION; FEATURE EXTRACTION; IMAGE CODING; LEARNING ALGORITHMS; UNSUPERVISED LEARNING;

ALIGNMENT TECHNIQUE; COMPETITIVE PERFORMANCE; FEATURE EXTRACTION ALGORITHMS; LOCAL ALIGNMENT; MANIFOLD LEARNING; MULTILINEAR EXTENSION; SPARSE REPRESENTATION; UNSUPERVISED LEARNING METHOD;

TENSORS;

ALGORITHM; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; FACE; FACTUAL DATABASE; HUMAN; LEARNING; PATTERN RECOGNITION; PHYSIOLOGY; PRINCIPAL COMPONENT ANALYSIS; PROCEDURES; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DATABASES, FACTUAL; FACE; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; LEARNING; LINEAR MODELS; PATTERN RECOGNITION, AUTOMATED; PATTERN RECOGNITION, VISUAL; PRINCIPAL COMPONENT ANALYSIS;

EID: 84907816910     PISSN: 2162237X     EISSN: 21622388     Source Type: Journal    
DOI: 10.1109/TNNLS.2013.2295717     Document Type: Article

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