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Marginalization in composed probabilistic models
- 1.0410574 - UTIA-B 20010043 RIV US eng C - Conference Paper (international conference)
Jiroušek, Radim
Marginalization in composed probabilistic models.
San Francisco: Morgan Kaufmann, 2000. ISBN 1-55860-709-9. In: Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence. - (Boutilier, C.; Goldszmidt, M.), s. 36-43
[Conference on Uncertainty in Artificial Intelligence /16./. Stanford (US), 30.06.2000-03.07.2000]
R&D Projects: GA ČR GA201/98/1487; GA MŠMT VS96008
Institutional research plan: AV0Z1075907
Keywords : multidimensional distribution * Bayesian network * computation
Subject RIV: BA - General Mathematics
Composition of low-dimensional distributions, whose foundations were laid in the paper published in the Proceedings of UAI'97, appeared to be an alternative apparatus to describe multidimensional probabilistic models. In contrast to Graphical Markov Models, which define multidimensional distributions in a declarative way, this approach is rather procedural.
Permanent Link: http://hdl.handle.net/11104/0130663
Number of the records: 1