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Volumn 6912 LNAI, Issue PART 2, 2011, Pages 581-596

Ancestor relations in the presence of unobserved variables

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN LEARNING; BAYESIAN NETWORKS (BNS); CONDITIONAL INDEPENDENCES; DATA ASSUMPTION; DYNAMIC PROGRAMMING ALGORITHM; MARKOV EQUIVALENCE CLASS; MAXIMUM A POSTERIORI; MISSPECIFICATION; NETWORK STRUCTURES; OBSERVATIONAL DATA; POSTERIOR PROBABILITY;

EID: 80052411766     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23783-6_37     Document Type: Conference Paper
Times cited : (13)

References (21)
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    • Cooper, G.F., Herskovits, E.: A Bayesian method for the induction of probabilistic networks from data. Machine Learning 9(4), 309-347 (1992)
    • (1992) Machine Learning , vol.9 , Issue.4 , pp. 309-347
    • Cooper, G.F.1    Herskovits, E.2
  • 4
    • 21844452434 scopus 로고    scopus 로고
    • Learning hidden variable networks: The information bottleneck approach
    • Elidan, G., Friedman, N.: Learning hidden variable networks: The information bottleneck approach. Journal of Machine Learning Research 6, 81-127 (2005)
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 81-127
    • Elidan, G.1    Friedman, N.2
  • 9
    • 0037262841 scopus 로고    scopus 로고
    • Being Bayesian about network structure: A Bayesian approach to structure discovery in Bayesian networks
    • Friedman, N., Koller, D.: Being Bayesian about network structure: A Bayesian approach to structure discovery in Bayesian networks. Machine Learning 50(1-2), 95-125 (2003)
    • (2003) Machine Learning , vol.50 , Issue.1-2 , pp. 95-125
    • Friedman, N.1    Koller, D.2
  • 10
    • 43049097125 scopus 로고    scopus 로고
    • Improving the structure MCMC sampler for Bayesian networks by int roducing a new edge reversal move
    • Grzegorczyk, M., Husmeier, D.: Improving the structure MCMC sampler for Bayesian networks by int roducing a new edge reversal move. Machine Learning 71, 265-305 (2008)
    • (2008) Machine Learning , vol.71 , pp. 265-305
    • Grzegorczyk, M.1    Husmeier, D.2
  • 11
    • 34249761849 scopus 로고
    • Learning Bayesian networks: The combination of knowledge and statistical data
    • Heckerman, D., Geiger, D., Chickering, D.M.: 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
  • 13
    • 0026822833 scopus 로고
    • Computational aspects of the Möbius transformation of graphs
    • Kennes, R.: Computational aspects of the Möbius transformation of graphs. IEEE Transaction on Systems, Man, and Cybernetics 22(2), 201-223 (1992)
    • (1992) IEEE Transaction on Systems, Man, and Cybernetics , vol.22 , Issue.2 , pp. 201-223
    • Kennes, R.1
  • 15
    • 31844439894 scopus 로고    scopus 로고
    • Exact Bayesian structure discovery in Bayesian networks
    • Koivisto, M., Sood, K.: Exact Bayesian structure discovery in Bayesian networks. Journal of Machine Learning Research 5, 549-573 (2004)
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 549-573
    • Koivisto, M.1    Sood, K.2
  • 16


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.