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Volumn , Issue , 2012, Pages

PAC-learning in the presence of one-sided classification noise

Author keywords

[No Author keywords available]

Indexed keywords

AXIS PARALLEL RECTANGLES; COMBINATORIAL PROBLEM; CONCEPT CLASS; LEARNING STRATEGY; LOWER BOUNDS; QUADRATIC TIME; SAMPLE SIZES; UNION-FIND DATA STRUCTURES;

EID: 84885764344     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (3)

References (24)
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    • A note on learning from multiple-instance examples
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    • Blum, A.1    Kalai, A.2
  • 8
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    • Solving the multiple instance problem with axis-parallel rectangles
    • Dietterich, T. G.; Lathrop, R. H.; and Lozano-Pérez, 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-Pérez, T.3
  • 11
    • 0002192516 scopus 로고
    • Decision theoretic generalizations of the PAC model for neural net and other learning applications
    • Haussler, D. 1992. Decision theoretic generalizations of the PAC model for neural net and other learning applications. Information and Computation 100(1):78-150.
    • (1992) Information and Computation , vol.100 , Issue.1 , pp. 78-150
    • Haussler, D.1
  • 12
    • 0027580356 scopus 로고
    • Very simple classification rules perform well on most commonly used datasets
    • Holte, R. C. 1993. Very simple classification rules perform well on most commonly used datasets. Machine Learning 11(1):63-90.
    • (1993) Machine Learning , vol.11 , Issue.1 , pp. 63-90
    • Holte, R.C.1
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    • 0032202014 scopus 로고    scopus 로고
    • Efficient noise-tolerant learning from statistical queries
    • Kearns, M. 1998. Efficient noise-tolerant learning from statistical queries. Journal of the Association on Computing Machinery 45(6):983-1006.
    • (1998) Journal of the Association on Computing Machinery , vol.45 , Issue.6 , pp. 983-1006
    • Kearns, M.1
  • 19
    • 0030128944 scopus 로고    scopus 로고
    • General bounds on the number of examples needed for learning probabilistic concepts
    • Simon, H. U. 1996. General bounds on the number of examples needed for learning probabilistic concepts. Journal of Computer and System Sciences 52(2):239-255.
    • (1996) Journal of Computer and System Sciences , vol.52 , Issue.2 , pp. 239-255
    • Simon, H.U.1
  • 20
    • 0021518106 scopus 로고
    • A theory of the learnable
    • Valiant, L. G. 1984. A theory of the learnable. Communications of the ACM 27(11):1134-1142.
    • (1984) Communications of the ACM , vol.27 , Issue.11 , pp. 1134-1142
    • Valiant, L.G.1
  • 23
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    • Maximizing the predictive value of production rules
    • Weiss, S. M.; Galen, R. S.; and Tadepalli, P. 1990. Maximizing the predictive value of production rules. Artificial Intelligence 45(1-2):47-71.
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    • Weiss, S.M.1    Galen, R.S.2    Tadepalli, P.3
  • 24
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    • Multi-instance learning based web mining
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.