Název: Representations of Bayesian Networks by Low-Rank Models
Autoři: Tichavský, Petr ; Vomlel, Jiří
Typ dokumentu: Příspěvky z konference
Konference/Akce: International Conference on Probabilistic Graphical Models, Praha (CZ), 20180911
Rok: 2018
Jazyk: eng
Abstrakt: Conditional probability tables (CPTs) of discrete valued random variables may achieve high dimensions and Bayesian networks defined as the product of these CPTs may become intractable by conventional methods of BN inference because of their dimensionality. In many cases, however, these probability tables constitute tensors of relatively low rank. Such tensors can be written in the so-called Kruskal form as a sum of rank-one components. Such representation would be equivalent to adding one artificial parent to all random variables and deleting all edges between the variables. The most difficult task is to find such a representation given a set of marginals or CPTs of the random variables under consideration. In the former case, it is a problem of joint canonical polyadic (CP) decomposition of a set of tensors. The latter fitting problem can be solved in a similar manner. We apply a recently proposed alternating direction method of multipliers (ADMM), which assures that the model has a probabilistic interpretation, i.e., that all elements of all factor matrices are nonnegative. We perform experiments with several well-known Bayesian networks.\n\n
Klíčová slova: canonical polyadic tensor decomposition; conditional probability tables; marginal probability tables
Číslo projektu: GA17-00902S (CEP)
Poskytovatel projektu: GA ČR
Zdrojový dokument: Proceedings of Machine Learning Research

Instituce: Ústav teorie informace a automatizace AV ČR (web)
Informace o dostupnosti dokumentu: Dokument je dostupný na externích webových stránkách.
Externí umístění souboru: http://library.utia.cas.cz/separaty/2018/SI/tichavsky-0493355.pdf
Původní záznam: http://hdl.handle.net/11104/0286997

Trvalý odkaz NUŠL: http://www.nusl.cz/ntk/nusl-386545


Záznam je zařazen do těchto sbírek:
Věda a výzkum > AV ČR > Ústav teorie informace a automatizace
Konferenční materiály > Příspěvky z konference
 Záznam vytvořen dne 2018-10-02, naposledy upraven 2021-11-24.


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