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Volumn , Issue , 2008, Pages 105-112

Bayesian network learning by compiling to weighted MAX-SAT

Author keywords

[No Author keywords available]

Indexed keywords

ACYCLICITY; BAYESIAN MODEL AVERAGING; BAYESIAN NETWORK LEARNING; DATA SETS; DATAPOINTS; INPUT FILES; LOCAL SEARCH ALGORITHM; MARGINAL LIKELIHOOD; MAX-SAT; MAX-SAT PROBLEMS; PRIOR INFORMATION; SUMMANDS; SYNTHETIC DATASETS; TOTAL ORDER;

EID: 77958576004     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (34)

References (8)
  • 1
  • 2
    • 0037262841 scopus 로고    scopus 로고
    • Being bayesian about network structure: A bayesian approach to structure discovery in bayesian networks
    • Nir Friedman and Daphne Koller. Being Bayesian about network structure: A Bayesian approach to structure discovery in Bayesian networks. Machine Learning, 50:95-126, 2003.
    • (2003) Machine Learning , vol.50 , pp. 95-126
    • Friedman, N.1    Koller, D.2
  • 3
    • 34249761849 scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • David Heckerman, Dan Geiger, and David M. Chickering. Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning, 20(3):197-243, 1995.
    • (1995) Machine Learning , vol.20 , Issue.3 , pp. 197-243
    • Heckerman, D.1    Geiger, D.2    Chickering, D.M.3
  • 4
    • 84950945692 scopus 로고
    • Model selection and accounting for model uncertainty in graphical models using Occam's window
    • David Madigan and Adrian E. Raftery. Model selection and accounting for model uncertainty in graphical models using Occam's window. Journal of the American Statistical Association, 89:1535-1546, 1994.
    • (1994) Journal of the American Statistical Association , vol.89 , pp. 1535-1546
    • Madigan, D.1    Raftery, A.E.2
  • 5
    • 33750705605 scopus 로고    scopus 로고
    • Sound and efficient inference with probabilistic and deterministic dependencies
    • Proceedings of the 21st National Conference on Artificial Intelligence and the 18th Innovative Applications of Artificial Intelligence Conference, AAAI-06/IAAI-06
    • Hoifung Poon and Pedro Domingos. Sound and efficient inference with probabilistic and deterministic dependencies. In Proc. AAAI-06, pages 458-463, 2006. (Pubitemid 44705326)
    • (2006) Proceedings of the National Conference on Artificial Intelligence , vol.1 , pp. 458-463
    • Poon, H.1    Domingos, P.2
  • 6
    • 33749541860 scopus 로고    scopus 로고
    • Solving Bayesian inference by weighted model counting
    • Pittsburgh
    • Tian Sang, Paul Beame, and Henry Kautz. Solving Bayesian inference by weighted model counting. In Proc. AAAI-05, Pittsburgh, 2005.
    • (2005) Proc. AAAI-05
    • Sang, T.1    Beame, P.2    Kautz, H.3
  • 7
    • 84880903318 scopus 로고    scopus 로고
    • A dynamic approach to MPE and weighted MAX-SAT
    • Hyderabad
    • Tian Sang, Paul Beame, and Henry Kautz. A dynamic approach to MPE and weighted MAX-SAT. In Proc. IJCAI-07, Hyderabad, 2007.
    • (2007) Proc. IJCAI-07
    • Sang, T.1    Beame, P.2    Kautz, H.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.