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Local parameter training of algebraic Bayesian networks : Conjugate distributions and expert knowledge with uncertainty. / Kharitonov, Nikita A.; Alexander, Tulupyev.

в: CEUR Workshop Proceedings, Том 2648, 2020, стр. 219-226.

Результаты исследований: Научные публикации в периодических изданиях › статья в журнале по материалам конференции › Рецензирование

Harvard

Kharitonov, NA & Alexander, T 2020, 'Local parameter training of algebraic Bayesian networks: Conjugate distributions and expert knowledge with uncertainty', CEUR Workshop Proceedings, Том. 2648, стр. 219-226.

APA

Kharitonov, N. A., & Alexander, T. (2020). Local parameter training of algebraic Bayesian networks: Conjugate distributions and expert knowledge with uncertainty. CEUR Workshop Proceedings, 2648, 219-226.

Vancouver

Kharitonov NA, Alexander T. Local parameter training of algebraic Bayesian networks: Conjugate distributions and expert knowledge with uncertainty. CEUR Workshop Proceedings. 2020;2648:219-226.

Author

Kharitonov, Nikita A. ; Alexander, Tulupyev. / Local parameter training of algebraic Bayesian networks : Conjugate distributions and expert knowledge with uncertainty. в: CEUR Workshop Proceedings. 2020 ; Том 2648. стр. 219-226.

BibTeX

@article{b3b4c1a2cead4ddab97dc30714a4bc12,
title = "Local parameter training of algebraic Bayesian networks: Conjugate distributions and expert knowledge with uncertainty",
abstract = "In the work the local parametric training of Algebraic Bayesian networks is considered. The theorem about the change of Dirichlet distribution parameters during transition from a priori to a posteriori probability distribution on propositional quantum formulas is formulated and proved. The proof is based on the conjugation property of the multinomial and Dirichlet distributions.",
keywords = "Algebraic Bayesian networks, Dirichlet distribution, Machine learning, Multinomial distribution, Parametric training, Probabilistic graphical models",
author = "Kharitonov, {Nikita A.} and Tulupyev Alexander",
note = "Publisher Copyright: {\textcopyright} 2020 Copyright for this paper by its authors.; 2020 {"}Russian Advances in Artificial Intelligence{"}, RAAI 2020 ; Conference date: 10-10-2020 Through 16-10-2020",
year = "2020",
language = "English",
volume = "2648",
pages = "219--226",
journal = "CEUR Workshop Proceedings",
issn = "1613-0073",
publisher = "RWTH Aahen University",

}

RIS

TY - JOUR

T1 - Local parameter training of algebraic Bayesian networks

T2 - 2020 "Russian Advances in Artificial Intelligence", RAAI 2020

AU - Kharitonov, Nikita A.

AU - Alexander, Tulupyev

N1 - Publisher Copyright: © 2020 Copyright for this paper by its authors.

PY - 2020

Y1 - 2020

N2 - In the work the local parametric training of Algebraic Bayesian networks is considered. The theorem about the change of Dirichlet distribution parameters during transition from a priori to a posteriori probability distribution on propositional quantum formulas is formulated and proved. The proof is based on the conjugation property of the multinomial and Dirichlet distributions.

AB - In the work the local parametric training of Algebraic Bayesian networks is considered. The theorem about the change of Dirichlet distribution parameters during transition from a priori to a posteriori probability distribution on propositional quantum formulas is formulated and proved. The proof is based on the conjugation property of the multinomial and Dirichlet distributions.

KW - Algebraic Bayesian networks

KW - Dirichlet distribution

KW - Machine learning

KW - Multinomial distribution

KW - Parametric training

KW - Probabilistic graphical models

UR - http://www.scopus.com/inward/record.url?scp=85092272122&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:85092272122

VL - 2648

SP - 219

EP - 226

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

SN - 1613-0073

Y2 - 10 October 2020 through 16 October 2020

ER -

ID: 88231323