Standard

Software implementation of reconciliation algorithms in algebraic Bayesian networks. / Kharitonov, Nikita A.; Tulupyev, Alexander L.; Zolotin, Andrey A.

Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017. ed. / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2017. p. 8-10 7970479.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Harvard

Kharitonov, NA, Tulupyev, AL & Zolotin, AA 2017, Software implementation of reconciliation algorithms in algebraic Bayesian networks. in S Shaposhnikov (ed.), Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017., 7970479, Institute of Electrical and Electronics Engineers Inc., pp. 8-10, 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017, St. Petersburg, Russian Federation, 24/05/17. https://doi.org/10.1109/SCM.2017.7970479

APA

Kharitonov, N. A., Tulupyev, A. L., & Zolotin, A. A. (2017). Software implementation of reconciliation algorithms in algebraic Bayesian networks. In S. Shaposhnikov (Ed.), Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017 (pp. 8-10). [7970479] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SCM.2017.7970479

Vancouver

Kharitonov NA, Tulupyev AL, Zolotin AA. Software implementation of reconciliation algorithms in algebraic Bayesian networks. In Shaposhnikov S, editor, Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 8-10. 7970479 https://doi.org/10.1109/SCM.2017.7970479

Author

Kharitonov, Nikita A. ; Tulupyev, Alexander L. ; Zolotin, Andrey A. / Software implementation of reconciliation algorithms in algebraic Bayesian networks. Proceedings of 2017 20th IEEE International Conference on Soft Computing and Measurements, SCM 2017. editor / S. Shaposhnikov. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 8-10

BibTeX

@inproceedings{cc384e7d21594f9ebb5972534353da31,
title = "Software implementation of reconciliation algorithms in algebraic Bayesian networks",
abstract = "Algorithms for algebraic Bayesian networks external and internal consistency maintenance are considered in the paper. An implementation of classes' structure representing algebraic Bayesian networks is proposed. The main approaches used in the consistency algorithms implementation as well as use cases of developed methods are provided. The proposed structure can later be re-used in the global inference algorithms implementation.",
keywords = "algebraic Bayesian networks, algprobabilistic graphical model, consistency check, machine learning",
author = "Kharitonov, {Nikita A.} and Tulupyev, {Alexander L.} and Zolotin, {Andrey A.}",
year = "2017",
month = jul,
day = "6",
doi = "10.1109/SCM.2017.7970479",
language = "English",
pages = "8--10",
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 - Software implementation of reconciliation algorithms in algebraic Bayesian networks

AU - Kharitonov, Nikita A.

AU - Tulupyev, Alexander L.

AU - Zolotin, Andrey A.

PY - 2017/7/6

Y1 - 2017/7/6

N2 - Algorithms for algebraic Bayesian networks external and internal consistency maintenance are considered in the paper. An implementation of classes' structure representing algebraic Bayesian networks is proposed. The main approaches used in the consistency algorithms implementation as well as use cases of developed methods are provided. The proposed structure can later be re-used in the global inference algorithms implementation.

AB - Algorithms for algebraic Bayesian networks external and internal consistency maintenance are considered in the paper. An implementation of classes' structure representing algebraic Bayesian networks is proposed. The main approaches used in the consistency algorithms implementation as well as use cases of developed methods are provided. The proposed structure can later be re-used in the global inference algorithms implementation.

KW - algebraic Bayesian networks

KW - algprobabilistic graphical model

KW - consistency check

KW - machine learning

UR - http://www.scopus.com/inward/record.url?scp=85027153746&partnerID=8YFLogxK

U2 - 10.1109/SCM.2017.7970479

DO - 10.1109/SCM.2017.7970479

M3 - Conference contribution

AN - SCOPUS:85027153746

SP - 8

EP - 10

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: 36985157