Low-rank quadratic semidefinite programming

Neurocomputing

Volumn 106, Issue , 2013, Pages 51-60

  Yuan, Ganzhao ^a   Zhang, Zhenjie ^b   Ghanem, Bernard ^c   Hao, Zhifeng ^a,d  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b Illinois at Singapore Pte   (Singapore)

^c KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Saudi Arabia)

^d GUANGDONG UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Eigenvalue decomposition; Kernel learning; Low rank and sparse matrix approximation; Metric learning; Semidefinite programming

Indexed keywords

EIGENVALUE DECOMPOSITION; KERNEL LEARNING; METRIC LEARNING; SEMI-DEFINITE PROGRAMMING; SPARSE MATRICES;

DISTANCE EDUCATION; EIGENVALUES AND EIGENFUNCTIONS; LEARNING SYSTEMS;

MATHEMATICAL PROGRAMMING;

ALGORITHM; ARTICLE; COMPUTER PROGRAM; CONTROLLED STUDY; DISTANCE LEARNING; INFORMATION PROCESSING; KERNEL METHOD; LOW RANK MATRIX APPROXIMATION; MACHINE LEARNING; PRIORITY JOURNAL; QUADRATIC SEMIDEFINITE PROGRAMMING; SPARSE MATRIX APPROXIMATION; TOP K EIGENVALUE; VALIDATION STUDY;

EID: 84875397094     PISSN: 09252312     EISSN: 18728286     Source Type: Journal    
DOI: 10.1016/j.neucom.2012.10.014     Document Type: Article

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