Prototype vector machine for large scale semi-supervised learning

ACM International Conference Proceeding Series

Volumn 382, Issue , 2009, Pages

  Zhang, Kai ^a   Kwok, James T ^b   Parvin, Bahram ^a  

^a LAWRENCE BERKELEY NATIONAL LABORATORY   (United States)

^b HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARK DATA; COMPUTATIONAL INTENSIVENESS; GRAPH-BASED; KERNEL MATRICES; LOW RANK APPROXIMATIONS; MACHINE-LEARNING; MINIMUM INFORMATION LOSS; MODEL REPRESENTATION; PROTOTYPE VECTORS; REGULARIZER; SCALING PROPERTIES; SEMI-SUPERVISED LEARNING; UNLABELED DATA;

COMPUTATIONAL EFFICIENCY; ROBOT LEARNING; SUPERVISED LEARNING;

EDUCATION;

EID: 70049106797     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1553374.1553531     Document Type: Conference Paper

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