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Volumn , Issue , 2007, Pages 217-224

Branch and bound for semi-supervised support vector machines

Author keywords

[No Author keywords available]

Indexed keywords

BRANCH AND BOUNDS; EMPIRICAL EVIDENCE; GENERALIZATION PERFORMANCE; LOCAL MINIMA PROBLEMS; LOW DENSITY; OPTIMAL SOLUTIONS; OPTIMIZATION PROBLEMS; SEMI-SUPERVISED; SMALL DATA SET;

EID: 84864069202     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (95)

References (17)
  • 9
    • 1942483137 scopus 로고    scopus 로고
    • Transductive inference for text classification using support vector machines
    • T. Joachims. Transductive inference for text classification using support vector machines. In International Conference on Machine Learning, 1999.
    • (1999) International Conference on Machine Learning
    • Joachims, T.1
  • 10
    • 0025673487 scopus 로고
    • Computational aspects of a branch and bound algorithm for quadratic zero-one programming
    • P.M. Pardalos and G.P. Rodgers. Computational aspects of a branch and bound algorithm for quadratic zero-one programming. Computing, 45:131-144, 1990.
    • (1990) Computing , vol.45 , pp. 131-144
    • Pardalos, P.M.1    Rodgers, G.P.2
  • 11
    • 41549135790 scopus 로고    scopus 로고
    • A taxonomy of semi-supervised learning methods
    • O. Chapelle, B. Schölkopf, and A. Zien, editors, MIT Press
    • M. Seeger. A taxonomy of semi-supervised learning methods. In O. Chapelle, B. Schölkopf, and A. Zien, editors, Semi-Supervised Lerning. MIT Press, 2006.
    • (2006) Semi-Supervised Lerning
    • Seeger, M.1
  • 14
    • 33749253228 scopus 로고
    • On structural risk minimization or overall risk in a problem of pattern recognition
    • V. Vapnik and A. Sterin. On structural risk minimization or overall risk in a problem of pattern recognition. Automation and Remote Control, 10(3):1495-1503, 1977.
    • (1977) Automation and Remote Control , vol.10 , Issue.3 , pp. 1495-1503
    • Vapnik, V.1    Sterin, A.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.