Search results

0477182 - ÚTIA 2018 RIV CH eng C - Conference Paper (international conference)
Vomlel, Jiří - Kratochvíl, Václav
Solving Trajectory Optimization Problems by Influence Diagrams.
Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2017. Cham: Springer, 2017 - (Antonucci, A.; Cholvy, L.; Papini, O.), s. 146-155. Lecture Notes in Computer Science, 10369. ISBN 978-3-319-61580-6.
[ECSQARU: European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty. Lugano (CH), 10.07.2017-14.07.2017]
R&D Projects: GA ČR(CZ) GA16-12010S; GA ČR GA17-08182S
Institutional support: RVO:67985556
Keywords : Influence diagrams * Probabilistic graphical models * Optimal control theory * Brachistochrone problem * Goddard problem
OECD category: Automation and control systems
http://library.utia.cas.cz/separaty/2017/MTR/vomlel-0477182.pdf
Permanent Link: http://hdl.handle.net/11104/0273650

0380991 - ÚTIA 2013 RIV ES eng C - Conference Paper (international conference)
Vomlel, Jiří - Tichavský, Petr
Computationally efficient probabilistic inference with noisy threshold models based on a CP tensor decomposition.
Proceedings of The Sixth European Workshop on Probabilistic Graphical Models. Granada: DECSAI, University of Granada, 2012, s. 355-362. ISBN 978-84-15536-57-4.
[The Sixth European Workshop on Probabilistic Graphical Models. Granada (ES), 19.09.2012-21.09.2012]
R&D Projects: GA ČR GA102/09/1278; GA ČR GA201/08/0539
Institutional support: RVO:67985556
Keywords : probabilistic graphical models * probabilistic inference * CP tensor decomposition
Subject RIV: JD - Computer Applications, Robotics
http://library.utia.cas.cz/separaty/2012/MTR/vomlel-computationally efficient probabilistic inference with noisy threshold models based on a cp tensor decomposition.pdf
Permanent Link: http://hdl.handle.net/11104/0211567

0085999 - ÚTIA 2008 RIV CZ eng C - Conference Paper (international conference)
Vomlel, Jiří - Studený, Milan
Using imsets for learning Bayesian networks.
[Využití imsetů při učení bayesovských sítí.]
Proceedings of Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty /10./. Praha: UTIA AV ČR, 2007 - (Kroupa, T.; Vejnarová, J.), s. 178-189
[Czech-Japan Seminar on Data Analysis and Decision Making under Uncertainty /10./. Liblice (CZ), 15.09.2007-18.09.2007]
R&D Projects: GA MŠMT(CZ) 1M0572
Grant - others:GA MŠk(CZ) 2C06019
Institutional research plan: CEZ:AV0Z10750506
Keywords : Bayesian networks * artificial intelligence * probabilistic graphical models * machine learning
Subject RIV: BB - Applied Statistics, Operational Research
Permanent Link: http://hdl.handle.net/11104/0148380