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Matrix-vector algorithms of global posteriori inference in algebraic Bayesian networks. / Zolotin, Andrey A.; Tulupyev, Alexander L.

Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017. ред. / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2017. стр. 22-24 7970483.

Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование

Harvard

Zolotin, AA & Tulupyev, AL 2017, Matrix-vector algorithms of global posteriori inference in algebraic Bayesian networks. в S Shaposhnikov (ред.), Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017., 7970483, Institute of Electrical and Electronics Engineers Inc., стр. 22-24, 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017, St. Petersburg, Российская Федерация, 24/05/17. https://doi.org/10.1109/SCM.2017.7970483

APA

Zolotin, A. A., & Tulupyev, A. L. (2017). Matrix-vector algorithms of global posteriori inference in algebraic Bayesian networks. в S. Shaposhnikov (Ред.), Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017 (стр. 22-24). [7970483] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SCM.2017.7970483

Vancouver

Zolotin AA, Tulupyev AL. Matrix-vector algorithms of global posteriori inference in algebraic Bayesian networks. в Shaposhnikov S, Редактор, Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. стр. 22-24. 7970483 https://doi.org/10.1109/SCM.2017.7970483

Author

Zolotin, Andrey A. ; Tulupyev, Alexander L. / Matrix-vector algorithms of global posteriori inference in algebraic Bayesian networks. Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017. Редактор / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2017. стр. 22-24

BibTeX

@inproceedings{5bdaa8e694364665a74da9a4a2006376,
title = "Matrix-vector algorithms of global posteriori inference in algebraic Bayesian networks",
abstract = "Algorithm of global posteriori inference in algebraic Bayesian networks is considered in the paper. The results obtained earlier for local a posteriori inference are briefly presented. Main steps of global propagation algorithm are described in details. A transition matrix from the vector of knowledge pattern elements to the virtual evidence, propagated to the next knowledge pattern, is proposed. The stated theorem describes the matrix-vector representation of the stochastic evidence propagation algorithm within a network with scalar estimates of the knowledge patterns elements probabilities of truth. The obtained results form the basis for development of the global posteriori inference machine matrix-vector representation in algebraic Bayesian networks and simplify its further software implementation.",
keywords = "algebraic Bayesian networks, global inference, ideal of conjuncts, matrix-vector equations, probabilistic graphical models",
author = "Zolotin, {Andrey A.} and Tulupyev, {Alexander L.}",
year = "2017",
month = jul,
day = "6",
doi = "10.1109/SCM.2017.7970483",
language = "English",
pages = "22--24",
editor = "S. Shaposhnikov",
booktitle = "Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",
note = "20th IEEE International Conference on Soft Computing and Measurements, SCM 2017 ; Conference date: 24-05-2017 Through 26-05-2017",

}

RIS

TY - GEN

T1 - Matrix-vector algorithms of global posteriori inference in algebraic Bayesian networks

AU - Zolotin, Andrey A.

AU - Tulupyev, Alexander L.

PY - 2017/7/6

Y1 - 2017/7/6

N2 - Algorithm of global posteriori inference in algebraic Bayesian networks is considered in the paper. The results obtained earlier for local a posteriori inference are briefly presented. Main steps of global propagation algorithm are described in details. A transition matrix from the vector of knowledge pattern elements to the virtual evidence, propagated to the next knowledge pattern, is proposed. The stated theorem describes the matrix-vector representation of the stochastic evidence propagation algorithm within a network with scalar estimates of the knowledge patterns elements probabilities of truth. The obtained results form the basis for development of the global posteriori inference machine matrix-vector representation in algebraic Bayesian networks and simplify its further software implementation.

AB - Algorithm of global posteriori inference in algebraic Bayesian networks is considered in the paper. The results obtained earlier for local a posteriori inference are briefly presented. Main steps of global propagation algorithm are described in details. A transition matrix from the vector of knowledge pattern elements to the virtual evidence, propagated to the next knowledge pattern, is proposed. The stated theorem describes the matrix-vector representation of the stochastic evidence propagation algorithm within a network with scalar estimates of the knowledge patterns elements probabilities of truth. The obtained results form the basis for development of the global posteriori inference machine matrix-vector representation in algebraic Bayesian networks and simplify its further software implementation.

KW - algebraic Bayesian networks

KW - global inference

KW - ideal of conjuncts

KW - matrix-vector equations

KW - probabilistic graphical models

UR - http://www.scopus.com/inward/record.url?scp=85027124475&partnerID=8YFLogxK

U2 - 10.1109/SCM.2017.7970483

DO - 10.1109/SCM.2017.7970483

M3 - Conference contribution

AN - SCOPUS:85027124475

SP - 22

EP - 24

BT - Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017

A2 - Shaposhnikov, S.

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017

Y2 - 24 May 2017 through 26 May 2017

ER -

ID: 36985044