Reducing the unlabeled sample complexity of semi-supervised multi-view learning

Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Volumn 2015-August, Issue , 2015, Pages 627-634

  Lan, Chao ^a   Huan, Jun ^a  

^a University of Kansas   (United States)

Author keywords

Multi view learning; Sample complexity; Semi supervised learning

Indexed keywords

ERRORS; SUPERVISED LEARNING; VIRTUAL REALITY;

GENERALIZATION ERROR; MULTI-VIEW LEARNING; PROBABLY APPROXIMATELY CORRECT; PROOF OF CONCEPT; SAMPLE COMPLEXITY; SAMPLE DISTRIBUTIONS; SEMI- SUPERVISED LEARNING; UNLABELED SAMPLES;

DATA MINING;

EID: 84954098544     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2783258.2783409     Document Type: Conference Paper

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