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Jirí Tumpach
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2020 – today
- 2023
- [c11]Jirí Tumpach, Jan Koza, Martin Holena:
Improving Optimization with Gaussian Processes in the Covariance Matrix Adaptation Evolution Strategy. ITAT 2023: 82-88 - [i2]Lukás Korel, Petr Pulc, Jirí Tumpach, Martin Holena:
Video Scene Location Recognition with Neural Networks. CoRR abs/2309.11928 (2023) - 2022
- [c10]Jirí Tumpach, Jan Koza, Martin Holena:
Neural-network-based estimation of normal distributions in black-box optimization. ESANN 2022 - [c9]Jan Kalina
, Jirí Tumpach, Martin Holena:
On Combining Robustness and Regularization in Training Multilayer Perceptrons over Small Data. IJCNN 2022: 1-8 - [i1]Zbynek Pitra, Jan Koza, Jirí Tumpach, Martin Holena:
Landscape Analysis for Surrogate Models in the Evolutionary Black-Box Context. CoRR abs/2203.11315 (2022) - 2021
- [c8]Zbynek Pitra, Marek Hanus, Jan Koza, Jirí Tumpach
Interaction between model and its evolution control in surrogate-assisted CMA evolution strategy. GECCO 2021: 528-536 - [c7]Jan Koza, Jirí Tumpach, Zbynek Pitra, Martin Holena:
Combining Gaussian Processes and Neural Networks in Surrogate Modelling for Covariance Matrix Adaptation Evolution Strategy. ITAT 2021: 29-38 - [c6]Lukás Korel, Petr Pulc, Jirí Tumpach, Martin Holena:
Video Scene Location Recognition with Neural Networks. ITAT 2021: 85-93 - [c5]Jirí Tumpach, Jan Kalina, Martin Holena:
A Comparison of Regularization Techniques for Shallow Neural NetworksTrained on Small Datasets. ITAT 2021: 94-103 - [c4]Jan Koza
Using Past Experience for Configuration of Gaussian Processes in Black-Box Optimization. LION 2021: 167-182 - [c3]Jirí Ruzicka, Jan Koza, Jirí Tumpach, Zbynek Pitra, Martin Holena:
Combining Gaussian Processes with Neural Networks for Active Learning in Optimization. IAL@PKDD/ECML 2021: 105-120 - 2020
- [c2]Jirí Tumpach
Online Malware Detection with Variational Autoencoders. ITAT 2020: 122-129
2010 – 2019
- 2019
- [c1]Jirí Tumpach
Deep Networks in Online Malware Detection. ITAT 2019: 90-98
Coauthor Index
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