Search results
- 1.0551866 - ÚTIA 2023 RIV GB eng J - Journal Article
Adam, L. - Mácha, V. - Šmídl, Václav - Pevný, T.
General framework for binary classification on top samples.
Optimization Methods & Software. Roč. 37, č. 5 (2022), s. 1636-1667. ISSN 1055-6788. E-ISSN 1029-4937
R&D Projects: GA ČR GA18-21409S
Institutional support: RVO:67985556
Keywords : general framework * classification * ranking * accuracy at the top * Neyman–Pearson * Pat&Mat
OECD category: Applied mathematics
Impact factor: 2.2, year: 2022
Method of publishing: Open access
http://library.utia.cas.cz/separaty/2022/AS/smidl-0551866.pdf https://www.tandfonline.com/doi/full/10.1080/10556788.2021.1965601
Permanent Link: https://hdl.handle.net/11104/0337818 - 2.0538109 - ÚFP 2021 RIV US eng J - Journal Article
Škvára, Vít - Šmídl, Václav - Pevný, T. - Seidl, Jakub - Havránek, Aleš - Tskhakaya, David
Detection of Alfvén Eigenmodes on COMPASS with Generative Neural Networks.
Fusion Science and Technology. Roč. 76, č. 8 (2020), s. 962-971. ISSN 1536-1055. E-ISSN 1943-7641
R&D Projects: GA ČR GA18-21409S; GA MŠMT(CZ) EF16_019/0000768
EU Projects: European Commission(XE) 633053 - EUROfusion
Institutional support: RVO:61389021 ; RVO:67985556
Keywords : Alfvén eigenmodes * generative models * neural networks * Tokamak
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8); Applied mathematics (UTIA-B)
Impact factor: 1.100, year: 2020
Method of publishing: Open access
https://www.tandfonline.com/doi/pdf/10.1080/15361055.2020.1820805?needAccess=true&
Permanent Link: http://hdl.handle.net/11104/0315921 - 3.0522404 - ÚI 2021 RIV GB eng J - Journal Article
Kopp, M. - Pevný, T. - Holeňa, Martin
Anomaly explanation with random forests.
Expert Systems With Applications. Roč. 149, 1 July (2020), č. článku 113187. ISSN 0957-4174. E-ISSN 1873-6793
R&D Projects: GA ČR GA17-01251S
Grant - others:GA ČR(CZ) GA18-21409S
Program: GA
Institutional support: RVO:67985807
Keywords : Anomaly detection * Anomaly explanation * Classification rules * Feature selection * Random forests
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Impact factor: 6.954, year: 2020
Method of publishing: Limited access
http://dx.doi.org/10.1016/j.eswa.2020.113187
Permanent Link: http://hdl.handle.net/11104/0306903