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- 1.0494463 - ÚI 2019 RIV CH eng C - Conference Paper (international conference)
Coufal, David
Superkernels for RBF Networks Initialization (Short Paper).
Artificial Neural Networks and Machine Learning – ICANN 2018. Proceedings, Part II. Cham: Springer, 2018 - (Kůrková, V.; Manolopoulos, Y.; Hammer, B.; Iliadis, L.; Maglogiannis, I.), s. 621-623. Lecture Notes in Computer Science, 11140. ISBN 978-3-030-01420-9.
[ICANN 2018. International Conference on Artificial Neural Networks /27./. Rhodes (GR), 04.10.2018-07.10.2018]
R&D Projects: GA ČR(CZ) GA18-23827S
Institutional support: RVO:67985807
Keywords : Regression task * Nonparametric estimation * Superkernel
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://link.springer.com/content/pdf/bbm%3A978-3-030-01421-6%2F1.pdf
Permanent Link: http://hdl.handle.net/11104/0287651File Download Size Commentary Version Access 0494463a.pdf 7 182.3 KB Publisher’s postprint require - 2.0475090 - ÚI 2018 RIV DE eng C - Conference Paper (international conference)
Kalina, Jan - Peštová, Barbora
Nonparametric Bootstrap Estimation for Implicitly Weighted Robust Regression.
Proceedings ITAT 2017: Information Technologies - Applications and Theory. Aachen & Charleston: Technical University & CreateSpace Independent Publishing Platform, 2017 - (Hlaváčová, J.), s. 78-85. CEUR Workshop Proceedings, V-1885. ISBN 978-1974274741. ISSN 1613-0073.
[ITAT 2017. Conference on Theory and Practice of Information Technologies - Applications and Theory /17./. Martinské hole (SK), 22.09.2017-26.09.2017]
R&D Projects: GA ČR GA17-01251S
Institutional support: RVO:67985807
Keywords : robust regression * nonlinear regression * nonparametric estimation
OECD category: Statistics and probability
http://ceur-ws.org/Vol-1885/78.pdf
Permanent Link: http://hdl.handle.net/11104/0271964File Download Size Commentary Version Access a0475090.pdf 1 698.8 KB Publisher’s postprint require - 3.0314055 - ÚTIA 2009 CZ eng I - Internal Report
Berlinet, A. - Vajda, Igor
Divergence Criteria for Improved Selection Rules.
Praha: ÚTIA AV ČR, 2008. 15 s. Interní publikace DAR - ÚTIA, 2008/5.
R&D Projects: GA MŠMT 1M0572
Institutional research plan: CEZ:AV0Z10750506
Keywords : density estimation * nonparametric estimation * information divergence
Subject RIV: BD - Theory of Information
http://library.utia.cas.cz/separaty/2008/SI/vajda-divergence%20criteria%20for%20improved%20selection%20rules.pdf
Permanent Link: http://hdl.handle.net/11104/0164687File Download Size Commentary Version Access 0314055.pdf 1 158.1 KB Other open-access