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Volumn 2005, Issue , 2005, Pages 329-334

An evolutionary approach to transduction in support vector machines

Author keywords

Genetic algorithm; Pattern classification; SVM; Transductive inference; TSVM

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; GENETIC ALGORITHMS; GLOBAL OPTIMIZATION; PATTERN RECOGNITION; RANDOM PROCESSES; SET THEORY;

EID: 33846951185     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICHIS.2005.21     Document Type: Conference Paper
Times cited : (9)

References (11)
  • 1
    • 0038731227 scopus 로고    scopus 로고
    • Y. Chen, G. Wang, and S. Dong. Learning with progressive transductive support vector machine. Pattern Recogn. Lett., 24(12): 1845-1855, 20.03.
    • Y. Chen, G. Wang, and S. Dong. Learning with progressive transductive support vector machine. Pattern Recogn. Lett., 24(12): 1845-1855, 20.03.
  • 2
    • 34249753618 scopus 로고
    • Support-vector networks
    • C. Cortes and V. Vapnik. Support-vector networks. Machine Learning, 20(3):273-297, 1995.
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 273-297
    • Cortes, C.1    Vapnik, V.2
  • 11
    • 3142681478 scopus 로고    scopus 로고
    • Learning with local and global consistency
    • Technical report, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany
    • D. Zhou, O. Bousquet, T. Lal, J. Weston, arid B. Schlkopf. Learning with local and global consistency. Technical report, Max Planck Institute for Biological Cybernetics, Tuebingen, Germany, 2003.
    • (2003)
    • Zhou, D.1    Bousquet, O.2    Lal, T.3    Weston, J.4    arid, B.5    Schlkopf6


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.