Low-rank representation with local constraint for graph construction

Neurocomputing

Volumn 122, Issue , 2013, Pages 398-405

  Zheng, Yaoguo ^a   Zhang, Xiangrong ^a   Yang, Shuyuan ^a   Jiao, Licheng ^a  

^a XIDIAN UNIVERSITY   (China)

Author keywords

Classification; Learning; Local regularization; Rank minimization; Semi supervised; Weighted 1 norm

Indexed keywords

LEARNING; LOCAL REGULARIZATION; LOW-RANK REPRESENTATIONS; PHYSICAL INTERPRETATION; RANK MINIMIZATIONS; SEMI-SUPERVISED; SEMI-SUPERVISED LEARNING; SIMILARITY COEFFICIENTS;

ALGORITHMS; CLASSIFICATION (OF INFORMATION);

SUPERVISED LEARNING;

ACCURACY; ARTICLE; CLASSIFICATION; CONCEPTUAL FRAMEWORK; CORRELATION COEFFICIENT; DATA ANALYSIS; EXPERIMENTAL STUDY; FACTUAL DATABASE; GRAPH ALGORITHM; INFORMATION PROCESSING; INTERMETHOD COMPARISON; LEARNING ALGORITHM; LEARNING THEORY; LOW RANK REPRESENTATION WITH LOCAL CONSTRAINT ALGORITHM; MATHEMATICAL COMPUTING; MATHEMATICAL PHENOMENA; MEASUREMENT; MEASUREMENT SIMILARITY; PRIORITY JOURNAL; PROCESS DEVELOPMENT; RELIABILITY;

EID: 84884202455     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2013.06.013     Document Type: Article

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