A semi-supervised approach for dimensionality reduction with distributional similarity

Neurocomputing

Volumn 103, Issue , 2013, Pages 210-221

  Zheng, Feng ^a   Song, Zhan ^a   Shao, Ling ^c   Chung, Ronald ^b   Jia, Kui ^a   Wu, Xinyu ^a  

^a SHENZHEN INSTITUTES OF ADVANCED TECHNOLOGY   (China)

^b CHINESE UNIVERSITY OF HONG KONG   (Hong Kong)

^c UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

Diffusion maps; Distributional similarity; Expectation Maximization; Label information; Manifold learning

Indexed keywords

CHARACTER RECOGNITION; DATA VISUALIZATION; DIFFUSION; LEARNING ALGORITHMS; MAXIMUM PRINCIPLE; SUPERVISED LEARNING;

DIFFUSION MAPS; DISTRIBUTIONAL SIMILARITIES; EXPECTATION - MAXIMIZATIONS; LABEL INFORMATION; MANIFOLD LEARNING;

CLASSIFICATION (OF INFORMATION);

ACCURACY; ALGORITHM; ARTICLE; CLASSIFICATION ALGORITHM; DATA ANALYSIS; EXPECTATION MAXIMIZATION ALGORITHM; HANDWRITING; IMAGE ANALYSIS; INTERMETHOD COMPARISON; LEARNING ALGORITHM; MATHEMATICAL MODEL; MULTIFACTOR DIMENSIONALITY REDUCTION; PRIORITY JOURNAL; PROBABILITY; SEMI SUPERVISED DIFFUSION MAP; SUPPORT VECTOR MACHINE; SYSTEMATIC ERROR; VALIDATION PROCESS;

EID: 84870388995     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.09.023     Document Type: Article

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