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Volumn 3720 LNAI, Issue , 2005, Pages 329-340

MCMC learning of Bayesian network models by Markov blanket decomposition

Author keywords

[No Author keywords available]

Indexed keywords

MARKOV PROCESSES; MATHEMATICAL MODELS; MONTE CARLO METHODS;

EID: 33646385607     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11564096_33     Document Type: Conference Paper
Times cited : (8)

References (13)
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    • Castelo, R.1    Kocka, T.2
  • 4
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    • Being Bayesian about network structure. A Bayesian approach to structure discovery in Bayesian networks
    • N. Friedman and D. Koller. Being Bayesian about network structure. A Bayesian approach to structure discovery in Bayesian networks. Machine Learning, 50(1-2):95-125, 2003.
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    • Improving Markov chain Monte Carlo model search for data mining
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    • Giudici, P.1    Castelo, R.2
  • 6
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    • Decomposable graphical gaussian model determination
    • P. Giudici and P. Green. Decomposable graphical gaussian model determination. Biometrika, 86(4):785-801, 1999.
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    • Giudici, P.1    Green, P.2
  • 7
    • 77956889087 scopus 로고    scopus 로고
    • Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
    • P. Green. Reversible jump Markov chain Monte Carlo computation and Bayesian model determination. Biometrika, 82:711-732, 1998.
    • (1998) Biometrika , vol.82 , pp. 711-732
    • Green, P.1
  • 8
    • 34249761849 scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • D. Heckerman, D. Geiger, and D.M. Chickering. Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning, 20:197-243, 1995.
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    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 9
    • 0002811779 scopus 로고    scopus 로고
    • Improved learning of Bayesian networks
    • D. Koller and J. Breese, editors
    • T. Kocka and R. Castelo. Improved learning of Bayesian networks. In D. Koller and J. Breese, editors, Proc. of the Conf. on Uncertainty in AI, pages 269-276, 2001.
    • (2001) Proc. of the Conf. on Uncertainty in AI , pp. 269-276
    • Kocka, T.1    Castelo, R.2
  • 10
    • 84950945692 scopus 로고
    • Model selection and accounting for model uncertainty in graphical models using Occam's window
    • D. Madigan and A. Raftery. Model selection and accounting for model uncertainty in graphical models using Occam's window. J. of the Am. Stat. Assoc., 89:1535-1546, 1994.
    • (1994) J. of the Am. Stat. Assoc. , vol.89 , pp. 1535-1546
    • Madigan, D.1    Raftery, A.2
  • 11
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    • Bayesian graphical models for discrete data
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    • Sequential updating of conditional probabilities on directed graphical structures
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    • Spiegelhalter, D.J.1    Lauritzen, S.L.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.