A Parallel Sampling Method for Bayesian Networks

Yoshiki Kobari, Masaomi Kimura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper describes the method to estimate probabilities on Bayesian belief networks (BNs). A BN has nodes showing random variables and shows cause and effect relationships among nodes as a graph. We calculate posterior probabilities, and then estimate the uncertain plural events. As one of the method for estimating probabilities in BN is stochastic sampling. The method has known as taking time to calculate as BN become larger and more complex. Therefore, this paper proposes a parallel sampling method on BN. Then a BN need efficiently dividing to generate samples in parallel, therefore we use community detection. The number of nodes, which have mutual dependence among nodes, is the least to use community detection. In addition, pipeline processing as generating samples, which have mutual dependence reduces waiting time causing by existing them.

Original languageEnglish
Title of host publicationProceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages113-117
Number of pages5
Volume2018-February
ISBN (Electronic)9781538629413
DOIs
Publication statusPublished - 2018 Feb 16
Event1st International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017 - Budapest, Hungary
Duration: 2017 Oct 202017 Oct 22

Other

Other1st International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017
CountryHungary
CityBudapest
Period17/10/2017/10/22

Fingerprint

Bayesian networks
Sampling
Random variables
Pipelines
Processing

Keywords

  • Bayesian networks
  • dataminig
  • parallel sampling

ASJC Scopus subject areas

  • Computer Science Applications
  • Artificial Intelligence

Cite this

Kobari, Y., & Kimura, M. (2018). A Parallel Sampling Method for Bayesian Networks. In Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017 (Vol. 2018-February, pp. 113-117). [8294170] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISCSIC.2017.11

A Parallel Sampling Method for Bayesian Networks. / Kobari, Yoshiki; Kimura, Masaomi.

Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017. Vol. 2018-February Institute of Electrical and Electronics Engineers Inc., 2018. p. 113-117 8294170.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kobari, Y & Kimura, M 2018, A Parallel Sampling Method for Bayesian Networks. in Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017. vol. 2018-February, 8294170, Institute of Electrical and Electronics Engineers Inc., pp. 113-117, 1st International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017, Budapest, Hungary, 17/10/20. https://doi.org/10.1109/ISCSIC.2017.11
Kobari Y, Kimura M. A Parallel Sampling Method for Bayesian Networks. In Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017. Vol. 2018-February. Institute of Electrical and Electronics Engineers Inc. 2018. p. 113-117. 8294170 https://doi.org/10.1109/ISCSIC.2017.11
Kobari, Yoshiki ; Kimura, Masaomi. / A Parallel Sampling Method for Bayesian Networks. Proceedings - 2017 International Symposium on Computer Science and Intelligent Controls, ISCSIC 2017. Vol. 2018-February Institute of Electrical and Electronics Engineers Inc., 2018. pp. 113-117
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