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- 1.0537238 - ÚGN 2021 RIV CH eng C - Conference Paper (international conference)
Pecha, Marek - Horák, David
Analyzing l1-loss and l2-loss Support Vector Machines Implemented in PERMON Toolbox.
Lecture Notes in Electrical Engineering. Vol. 554. Cham: Springer Nature Switzerland AG, 2020 - (Zelinka, I.; Brandstetter, P.; Trong Dao, T.; Hoang Duy, V.; Kim, S.), s. 13-23. ISBN 978-3-030-14906-2. ISSN 1876-1100. E-ISSN 1876-1119.
[International Conference on Advanced Engineering Theory and Applications 2018 /5./. Ostrava (CZ), 11.11.2018-13.11.2018]
R&D Projects: GA MŠMT LQ1602
Institutional support: RVO:68145535
Keywords : Support Vector Machines * PermonSVM * Hinge loss functions * quadratic programming * MPRGP
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://link.springer.com/chapter/10.1007/978-3-030-14907-9_2
Permanent Link: http://hdl.handle.net/11104/0314975 - 2.0537236 - ÚGN 2021 RIV CH eng C - Conference Paper (international conference)
Domesová, Simona
The use of radial basis function surrogate models for sampling process acceleration in Bayesian inversio.
Lecture Notes in Electrical Engineering. Vol. 554. Cham: Springer Nature Switzerland AG, 2020 - (Zelinka, I.; Brandstetter, P.; Trong Dao, T.; Hoang Duy, V.; Kim, S.), s. 228-238. ISBN 978-3-030-14906-2. ISSN 1876-1100. E-ISSN 1876-1119.
[International Conference on Advanced Engineering Theory and Applications 2018 /5./. Ostrava (CZ), 11.11.2018-13.11.2018]
R&D Projects: GA MŠMT LQ1602
Institutional support: RVO:68145535
Keywords : Bayesian inversion * Metropolis-Hastings * radial basis functions * surrogate model * uncertainty quantification
OECD category: Applied mathematics
https://link.springer.com/chapter/10.1007%2F978-3-030-14907-9_23
Permanent Link: http://hdl.handle.net/11104/0314976File Download Size Commentary Version Access UGN_0537236.pdf 1 528.6 KB Author’s postprint require - 3.0537200 - ÚGN 2021 RIV CH eng C - Conference Paper (international conference)
Béreš, Michal
An Efficient Reduced Basis Construction for Stochastic Galerkin Matrix Equations Using Deflated Conjugate Gradients.
Lecture Notes in Electrical Engineering. Vol. 554. Cham: Springer Nature Switzerland AG, 2020 - (Zelinka, I.; Brandstetter, P.; Trong Dao, T.; Hoang Duy, V.; Kim, S.), s. 175-184. ISBN 978-3-030-14906-2. ISSN 1876-1100. E-ISSN 1876-1119.
[International Conference on Advanced Engineering Theory and Applications 2018 /5./. Ostrava (CZ), 11.11.2018-13.11.2018]
R&D Projects: GA MŠMT LQ1602
Institutional support: RVO:68145535
Keywords : stochastic Galerkin method * reduced basis method * deflated conjugate gradients method * darcy flow problem
OECD category: Applied mathematics
https://link.springer.com/chapter/10.1007/978-3-030-14907-9_18
Permanent Link: http://hdl.handle.net/11104/0314977File Download Size Commentary Version Access UGN_0537200.pdf 2 370.3 KB Author’s postprint require