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Volumn , Issue , 2002, Pages 943-944

Multiple instance learning with generalized support vector machines

Author keywords

[No Author keywords available]

Indexed keywords

HEURISTIC METHODS; LEARNING ALGORITHMS; LEARNING SYSTEMS; PROBLEM SOLVING;

EID: 0036923345     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (87)

References (11)
  • 1
    • 0002469253 scopus 로고    scopus 로고
    • On learning from multi-instance examples: Empirical evaluation of a theoretical approach
    • Morgan Kaufmann
    • Auer, P. 1997. On learning from multi-instance examples: Empirical evaluation of a theoretical approach. In Proc. 14th International Conference on Machine Learning, 21-29. Morgan Kaufmann.
    • (1997) Proc. 14th International Conference on Machine Learning , pp. 21-29
    • Auer, P.1
  • 3
    • 0012297834 scopus 로고    scopus 로고
    • Optimization approaches to semisupervised learning
    • Ferris, M.; Mangasarian, O.; and Pang, J., eds., Kluwer Academic Publishers, Boston
    • Demirez, A., and Bennett, K. 2000. Optimization approaches to semisupervised learning. In Ferris, M.; Mangasarian, O.; and Pang, J., eds., Applications and Algorithms of Complementarity. Kluwer Academic Publishers, Boston.
    • (2000) Applications and Algorithms of Complementarity
    • Demirez, A.1    Bennett, K.2
  • 4
    • 0030649484 scopus 로고    scopus 로고
    • Solving the multiple instance problem with axis-parallel rectangles
    • Dietterich, T. G.; Lathrop, R. H.; and Lozano-Perez, T. 1997. Solving the multiple instance problem with axis-parallel rectangles. Artificial Intelligence 89(1-2):31-71.
    • (1997) Artificial Intelligence , vol.89 , Issue.1-2 , pp. 31-71
    • Dietterich, T.G.1    Lathrop, R.H.2    Lozano-Perez, T.3
  • 5
    • 0001938951 scopus 로고    scopus 로고
    • Transductive inference for text classification using support vector machines
    • Morgan Kaufmann, San Francisco, CA
    • Joachims, T. 1999. Transductive inference for text classification using support vector machines. In Proc. 16th International Conf. on Machine Learning, 200-209. Morgan Kaufmann, San Francisco, CA.
    • (1999) Proc. 16th International Conf. on Machine Learning , pp. 200-209
    • Joachims, T.1
  • 6
    • 0030384463 scopus 로고    scopus 로고
    • PAC learning axis aligned rectangles with respect to product distributions from multiple-instance examples
    • Long, P., and Tan, L. 1996. PAC learning axis aligned rectangles with respect to product distributions from multiple-instance examples. In Proceedings of the Conference on Computational Learning Theory, 228-234.
    • (1996) Proceedings of the Conference on Computational Learning Theory , pp. 228-234
    • Long, P.1    Tan, L.2
  • 7
    • 84898935332 scopus 로고    scopus 로고
    • A framework for multiple-instance learning
    • Jordan, M. I.; Kearns, M. J.; and Solla, S. A., eds., The MIT Press
    • Maron, O., and Lozano-Pérez, T. 1998. A framework for multiple-instance learning. In Jordan, M. I.; Kearns, M. J.; and Solla, S. A., eds., Advances in Neural Information Processing Systems, volume 10. The MIT Press.
    • (1998) Advances in Neural Information Processing Systems , vol.10
    • Maron, O.1    Lozano-Pérez, T.2
  • 8
    • 0002288190 scopus 로고    scopus 로고
    • Multiple-instance learning for natural scene classification
    • Morgan Kaufmann, San Francisco, CA
    • Maron, O., and Ratan, A. L. 1998. Multiple-instance learning for natural scene classification. In Proc. 15th International Conf. on Machine Learning, 341-349. Morgan Kaufmann, San Francisco, CA.
    • (1998) Proc. 15th International Conf. on Machine Learning , pp. 341-349
    • Maron, O.1    Ratan, A.L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.