Training Lp norm multiple kernel learning in the primal

Neural Networks

Volumn 46, Issue , 2013, Pages 172-182

  Liang, Zhizheng ^a   Xia, Shixiong ^a   Zhou, Yong ^a   Zhang, Lei ^a  

^a CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

Author keywords

Data classification; Empirical Rademacher complexity; Manifold regularization; Multiple kernel learning; Primal optimization

Indexed keywords

ALTERNATING OPTIMIZATIONS; DATA CLASSIFICATION; KERNEL WEIGHT; LEARNING THE KERNEL; MANIFOLD REGULARIZATIONS; MULTIPLE KERNEL LEARNING; PRECONDITIONED CONJUGATE GRADIENT METHOD; RADEMACHER COMPLEXITY;

SUPPORT VECTOR MACHINES;

OPTIMIZATION;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; DATA ANALYSIS; EMPIRICAL RADEMACHER COMPLEXITY; FEASIBILITY STUDY; INTERMETHOD COMPARISON; KERNEL WEIGHT; MACHINE LEARNING; MATHEMATICAL PARAMETERS; METHODOLOGY; MULTIPLE KERNEL LEARNING; PRIORITY JOURNAL; RADEMACHER COMPLEXITY THEORY; STATISTICAL ANALYSIS; THEORY;

DATA CLASSIFICATION; EMPIRICAL RADEMACHER COMPLEXITY; MANIFOLD REGULARIZATION; MULTIPLE KERNEL LEARNING; PRIMAL OPTIMIZATION;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; MODELS, THEORETICAL; PATTERN RECOGNITION, AUTOMATED; STATISTICS AS TOPIC;

EID: 84879556490     PISSN: 08936080     EISSN: 18792782     Source Type: Journal    
DOI: 10.1016/j.neunet.2013.05.003     Document Type: Article

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