Significant vector learning to construct sparse kernel regression models

Neural Networks

Volumn 20, Issue 7, 2007, Pages 791-798

  Gao, Junbin ^a   Shi, Daming ^b   Liu, Xiaomao ^c  

^a CHARLES STURT UNIVERSITY   (Australia)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^c HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Orthogonal least square; Relevance vector machine; Significant vector machine; Sparse kernel regression

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; REGRESSION ANALYSIS;

ORTHOGONAL LEAST SQUARE; RELEVANCE VECTOR MACHINE; SIGNIFICANT VECTOR MACHINE; SPARSE KERNEL REGRESSION;

LEARNING SYSTEMS;

ANALYTIC METHOD; ARTICLE; KERNEL METHOD; LEARNING ALGORITHM; MATHEMATICAL MODEL; ORTHOGONAL LEAST SQUARE; PRIORITY JOURNAL; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; REGRESSION ANALYSIS;

EID: 34548455315     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2007.03.001     Document Type: Article

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