Search results
- 1.0531044 - ÚTIA 2022 RIV SG eng C - Conference Paper (international conference)
Kratochvíl, Václav - Bína, Vladislav - Jiroušek, Radim - Lee, T. R.
Compositional Models: Iterative Structure Learning from Data.
Sensor Networks and Signal Processing. vol. 176. Singapore: Springer, 2021 - (Peng, S.; Favorskaya, M.; Chao, H.), s. 379-395. 2190-3018. ISBN 978-981-15-4916-8.
[Sensor Networks and Signal Processing (SNSP 2019) /2./. Hualien (TW), 19.11.2019-22.11.2019]
Grant - others:GA ČR(CZ) GA19-06569S; Akademie věd - GA AV ČR(CZ) MOST-04-18
Program: GA
Institutional support: RVO:67985556
Keywords : Compositional models * Structure learning * Decomposability * Likelihood-ratio * Test statistics
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
http://library.utia.cas.cz/separaty/2020/MTR/kratochvil-0531044.pdf
Permanent Link: http://hdl.handle.net/11104/0310094 - 2.0477168 - ÚTIA 2018 RIV US eng J - Journal Article
Djordjilović, V. - Chiogna, M. - Vomlel, Jiří
An empirical comparison of popular structure learning algorithms with a view to gene network inference.
International Journal of Approximate Reasoning. Roč. 88, č. 1 (2017), s. 602-613. ISSN 0888-613X. E-ISSN 1873-4731
R&D Projects: GA ČR(CZ) GA16-12010S
Institutional support: RVO:67985556
Keywords : Bayesian networks * Structure learning * Reverse engineering * Gene networks
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 1.766, year: 2017
http://library.utia.cas.cz/separaty/2017/MTR/vomlel-0477168.pdf
Permanent Link: http://hdl.handle.net/11104/0273649 - 3.0404628 - UIVT-O 20020040 RIV NL eng C - Conference Paper (international conference)
Coufal, David
Incremental Structure Learning of Three-Layered Gaussian RBF Networks.
Computational Science. Berlin: Springer, 2002 - (Sloot, P.; Tan, C.; Dongarra, J.; Hoekstra, A.), s. 584-593. Lecture Notes in Computer Science, 2331. ISBN 3-540-43594-8. ISSN 0302-9743.
[ICCS 2002. International Conference. Amsterdam (NL), 21.04.2002-24.04.2002]
R&D Projects: GA ČR GA201/00/1489
Keywords : structure learning * RBF networks * incremental learning
Subject RIV: BA - General Mathematics
Permanent Link: http://hdl.handle.net/11104/0124870 - 4.0404559 - UIVT-O 20010176 CZ eng V - Research Report
Coufal, David
Incremental Structure Learning of Wang Neuro-Fuzzy System.
Prague: ICS AS CR, 2001. 7 s. Technical Report, V-856.
R&D Projects: GA ČR GA201/00/1489
Institutional research plan: AV0Z1030915
Keywords : structure learning * neuro-fuzzy system * incremental learning algorithm
Subject RIV: BA - General Mathematics
Permanent Link: http://hdl.handle.net/11104/0124807 - 5.0103435 - UIVT-O 20040176 DE eng A - Abstract
Šimeček, Petr
Structure Learning with Small Amount of Statistical Data.
Computational Statistics. Book of Abstracts. Prague: Czech Statistical Society, 2004 - (Antoch, J.). s. 315. ISBN 80-239-3459-7.
[COMPSTAT 2004. Symposium /16./. 23.08.2004-27.08.2004, Prague]
R&D Projects: GA MŠMT LN00B107
Keywords : Bayesian networks * compositional models * structure learning
Subject RIV: BA - General Mathematics
Permanent Link: http://hdl.handle.net/11104/0010743 - 6.0041397 - ÚTIA 2007 CZ eng K - Conference Paper (Czech conference)
Šimeček, Petr
A Short Note on Structure Learning.
Proceedings of Contributed Papers. WDS''04. Praha: MATFYZPRESS, 2004 - (Šafránková, J.), s. 84-87. ISBN 80-86732-32-0.
[Week of Doctoral Students 2004. Prague (CZ), 15.06.2004-18.06.2004]
Institutional research plan: CEZ:AV0Z10750506
Keywords : graphical models * structure learning
Subject RIV: BD - Theory of Information
Permanent Link: http://hdl.handle.net/11104/0134875