Probabilistic inference with noisy-threshold models based on a CP tensor decomposition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F14%3A00427059" target="_blank" >RIV/67985556:_____/14:00427059 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.ijar.2013.12.002" target="_blank" >http://dx.doi.org/10.1016/j.ijar.2013.12.002</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.ijar.2013.12.002" target="_blank" >10.1016/j.ijar.2013.12.002</a>
Alternative languages
Result language
angličtina
Original language name
Probabilistic inference with noisy-threshold models based on a CP tensor decomposition
Original language description
The specification of conditional probability tables (CPTs) is a difficult task in the construction of probabilistic graphical models. Several types of canonical models have been proposed to ease that difficulty. Noisy-threshold models generalize the twomost popular canonical models: the noisy-or and the noisy-and. When using the standard inference techniques the inference complexity is exponential with respect to the number of parents of a variable. More efficient inference techniques can be employed for CPTs that take a special form. CPTs can be viewed as tensors. Tensors can be decomposed into linear combinations of rank-one tensors, where a rank-one tensor is an outer product of vectors. Such decomposition is referred to as Canonical Polyadic (CP)or CANDECOMP-PARAFAC (CP) decomposition. The tensor decomposition offers a compact representation of CPTs which can be efficiently utilized in probabilistic inference.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
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
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
International Journal of Approximate Reasoning
ISSN
0888-613X
e-ISSN
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Volume of the periodical
55
Issue of the periodical within the volume
4
Country of publishing house
US - UNITED STATES
Number of pages
21
Pages from-to
1072-1092
UT code for WoS article
000334087400010
EID of the result in the Scopus database
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