Group lasso regularized multiple kernel learning for heterogeneous feature selection

Proceedings of the International Joint Conference on Neural Networks

Volumn , Issue , 2011, Pages 2570-2577

  Yeh, Yi Ren ^a   Chung, Yung Yu ^b   Lin, Ting Chu ^a   Wang, Yu Chiang Frank ^a  

^a RESEARCH CENTER FOR INFORMATION TECHNOLOGY INNOVATION   (Taiwan)

^b Iowa State University of Science and Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION PERFORMANCE; COMPACT SETS; DATA SETS; FEATURE SELECTION METHODS; FEATURE SPACE; FEATURE SUBSET; HETEROGENEOUS DOMAINS; HETEROGENEOUS FEATURES; KERNEL PARAMETER; MULTIPLE KERNEL LEARNING; OPTIMAL SIZE; PRIOR KNOWLEDGE; RECOGNITION PERFORMANCE; REGULARIZER;

ALGORITHMS; CLASSIFICATION (OF INFORMATION); NEURAL NETWORKS; OPTIMIZATION;

FEATURE EXTRACTION;

EID: 80054762064     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2011.6033554     Document Type: Conference Paper

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