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Volumn 4212 LNAI, Issue , 2006, Pages 234-245

EM algorithm, for symmetric causal independence models

Author keywords

[No Author keywords available]

Indexed keywords

BOOLEAN FUNCTIONS; LEARNING ALGORITHMS; MATHEMATICAL MODELS; PROBABILITY;

EID: 33750341004     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11871842_25     Document Type: Conference Paper
Times cited : (4)

References (20)
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    • Exploiting causal independence in bayesian networks inference
    • Zhang, N.L., Poole, D.: Exploiting Causal Independence in Bayesian Networks Inference. Journal of Artificial Intelligence Research, Vol. 5 (1996) 301-328
    • (1996) Journal of Artificial Intelligence Research , vol.5 , pp. 301-328
    • Zhang, N.L.1    Poole, D.2
  • 6
    • 0026056182 scopus 로고
    • Probabilistic diagnosis using a reformulation of the INTERNIST-1/QMR knowledge base, i - The probabilistic model and inference algorithms
    • Shwe, M.A., Middleton, B., Heckerman, D.E., Henrion, M., Horvitz, E.J., Lehmann, H.P., Cooper, G.F.: Probabilistic Diagnosis using a Reformulation of the INTERNIST-1/QMR Knowledge Base, I - The Probabilistic Model and Inference Algorithms. Methods of Information in Medicine, Vol. 30 (1991) 241-255
    • (1991) Methods of Information in Medicine , vol.30 , pp. 241-255
    • Shwe, M.A.1    Middleton, B.2    Heckerman, D.E.3    Henrion, M.4    Horvitz, E.J.5    Lehmann, H.P.6    Cooper, G.F.7
  • 8
    • 14544288172 scopus 로고    scopus 로고
    • Bayesian network modelling through qualitative patterns
    • Lucas, P.J.F.: Bayesian Network Modelling Through Qualitative Patterns. Artificial Intelligence, Vol. 163 (2005) 233-263
    • (2005) Artificial Intelligence , vol.163 , pp. 233-263
    • Lucas, P.J.F.1
  • 9
    • 33750342507 scopus 로고    scopus 로고
    • Noisy threshold functions for modelling causal independence in bayesian networks
    • Radboud University Nijmegen
    • Jurgelenaite, R., Lucas, P.J.F., Heskes, T.: Noisy Threshold Functions for Modelling Causal Independence in Bayesian Networks. Technical report ICIS-R06014, Radboud University Nijmegen (2006)
    • (2006) Technical Report ICIS-R06014
    • Jurgelenaite, R.1    Lucas, P.J.F.2    Heskes, T.3
  • 12
    • 0000045489 scopus 로고
    • Some practical issues in constructing belief networks
    • Henrion, M.: Some Practical Issues in Constructing Belief Networks. Uncertainty in Artificial Intelligence, Vol. 3 (1989) 161-173
    • (1989) Uncertainty in Artificial Intelligence , vol.3 , pp. 161-173
    • Henrion, M.1
  • 15
    • 0001043914 scopus 로고
    • An approximation theorem for the poisson binomial distribution
    • Le Cam, L.: An Approximation Theorem for the Poisson Binomial Distribution. Pacific Journal of Mathematics, Vol. 10 (1960) 1181-1197
    • (1960) Pacific Journal of Mathematics , vol.10 , pp. 1181-1197
    • Le Cam, L.1
  • 17
    • 0010999002 scopus 로고
    • On the distribution of the number of successes in independent trials
    • Darroch, J.: On the Distribution of the Number of Successes in Independent Trials. The Annals of Mathematical Statistics, Vol. 35 (1964) 1317-1321
    • (1964) The Annals of Mathematical Statistics , vol.35 , pp. 1317-1321
    • Darroch, J.1
  • 18
    • 0031660017 scopus 로고    scopus 로고
    • Computer-based decision support in management of primary gastric non-hodgkin lymphoma
    • Lucas, P.J.F., Boot, H., Taal, B.: Computer-based Decision Support in Management of Primary Gastric non-Hodgkin Lymphoma. Methods of Information in Medicine, Vol. 37 (1998) 206-219
    • (1998) Methods of Information in Medicine , vol.37 , pp. 206-219
    • Lucas, P.J.F.1    Boot, H.2    Taal, B.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.