Manifold-preserving graph reduction for sparse semi-supervised learning

Neurocomputing

Volumn 124, Issue , 2014, Pages 13-21

  Sun, Shiliang ^a   Hussain, Zakria ^b   Shawe Taylor, John ^b  

^a EAST CHINA NORMAL UNIVERSITY   (China)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

Author keywords

Graph reduction; Semi supervised learning; Sparsity; Statistical learning theory; Support vector machine

Indexed keywords

APPROXIMATION RATIOS; GENERALIZATION ERROR; GRAPH REDUCTION; RADEMACHER COMPLEXITY; SEMI-SUPERVISED LEARNING; SPARSITY; STATISTICAL LEARNING THEORY; SUPPORT VECTOR MACHINE (SVMS);

APPROXIMATION ALGORITHMS; CLASSIFICATION (OF INFORMATION); LAPLACE TRANSFORMS; SUPERVISED LEARNING; SUPPORT VECTOR MACHINES;

GRAPH THEORY;

ARTICLE; INFORMATION PROCESSING; LEARNING ALGORITHM; MANIFOLD PRESERVING GRAPH REDUCTION ALGORITHM; MANIFOLD PRESERVING SPARSE GRAPH; MATHEMATICAL ANALYSIS; PRIORITY JOURNAL; PROCESS OPTIMIZATION; SEMI SUPERVISED LEARNING; SPARSE LAPLACIAN SUPPORT VECTOR MACHINE; SUPPORT VECTOR MACHINE;

EID: 84885841484     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.08.070     Document Type: Article

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