Probabilistic Inference in BN2T Models by Weighted Model Counting
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F13%3A00399130" target="_blank" >RIV/67985556:_____/13:00399130 - isvavai.cz</a>
Alternative codes found
RIV/61384399:31160/13:00043526
Result on the web
<a href="http://dx.doi.org/10.3233/978-1-61499-330-8-275" target="_blank" >http://dx.doi.org/10.3233/978-1-61499-330-8-275</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3233/978-1-61499-330-8-275" target="_blank" >10.3233/978-1-61499-330-8-275</a>
Alternative languages
Result language
angličtina
Original language name
Probabilistic Inference in BN2T Models by Weighted Model Counting
Original language description
Exact inference in Bayesian networks with nodes having a large parent set is not tractable using standard techniques as are the junction tree method or the variable elimination. However, in many applications, the conditional probability tbles of these nodes have certain local structure than can be exploited to make the exact inference tractable. In this paper we combine the CP tensor decomposition of probability tables with probabilistic inference using weighted model counting. The motivation for this combination is to exploit not only the local structure of some conditional probability tables but also other structural information potentialy present in the Baysian network, like determinism or context specific independence. We illustrate the proposed combination on BN2T networks -- two-layered Bayesian networks with conditional probability tables representing noisy threshold models.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Twelfth Scandinavian Conference on Artificial Intelligence
ISBN
978-1-61499-329-2
ISSN
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e-ISSN
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Number of pages
10
Pages from-to
275-284
Publisher name
IOS Press
Place of publication
Amsterdam
Event location
Aalborg
Event date
Nov 20, 2013
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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