| Gaussian process surrogate models for the CMA evolution strategy L Bajer, Z Pitra, J Repický, M Holeňa Evolutionary computation 27 (4), 665-697, 2019 | 56 | 2019 |
| Benchmarking gaussian processes and random forests surrogate models on the BBOB noiseless testbed L Bajer, Z Pitra, M Holeňa Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015 | 53 | 2015 |
| Machine learning classification of first-episode schizophrenia spectrum disorders and controls using whole brain white matter fractional anisotropy P Mikolas, J Hlinka, A Škoch, Z Pitra, T Frodl, F Spaniel, T Hájek BMC psychiatry 18 (1), 97, 2018 | 45 | 2018 |
| Doubly Trained Evolution Control for the Surrogate CMA-ES Z Pitra, L Bajer, M Holeňa International Conference on Parallel Problem Solving from Nature, 59-68, 2016 | 29 | 2016 |
| Overview of surrogate-model versions of covariance matrix adaptation evolution strategy Z Pitra, L Bajer, J Repický, M Holeňa Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2017 | 23 | 2017 |
| Landscape analysis of Gaussian process surrogates for the covariance matrix adaptation evolution strategy Z Pitra, J Repický, M Holeňa Proceedings of the Genetic and Evolutionary Computation Conference, 691-699, 2019 | 19 | 2019 |
| Interaction between model and its evolution control in surrogate-assisted CMA evolution strategy Z Pitra, M Hanuš, J Koza, J Tumpach, M Holeňa Proceedings of the Genetic and Evolutionary Computation Conference, 528-536, 2021 | 10 | 2021 |
| Comparing SVM, Gaussian Process and Random Forest Surrogate Models for the CMA-ES. Z Pitra, L Bajer, M Holeňa ITAT 2015, 186-193, 2015 | 9 | 2015 |
| Comparison of ordinal and metric Gaussian process regression as surrogate models for CMA evolution strategy Z Pitra, L Bajer, J Repický, M Holeňa Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2017 | 6 | 2017 |
| Knowledge-based Selection of Gaussian Process Surrogates Z Pitra, L Bajer, M Holeňa ECML PKDD 2019: Workshop on Interactive Adaptive Learning 2444, 48-63, 2019 | 5 | 2019 |
| Using past experience for configuration of Gaussian processes in Black-Box Optimization J Koza, J Tumpach, Z Pitra, M Holeňa International Conference on Learning and Intelligent Optimization, 167-182, 2021 | 4 | 2021 |
| Gaussian process surrogate models for the CMA-ES L Bajer, Z Pitra, J Repický, M Holeňa Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019 | 4 | 2019 |
| Automated Selection of Covariance Function for Gaussian Process Surrogate Models J Repický, Z Pitra, M Holeňa ITAT 2018 Proceedings 2203, 64-71, 2018 | 4 | 2018 |
| Boosted Regression Forest for the Doubly Trained Surrogate Covariance Matrix Adaptation Evolution Strategy Z Pitra, J Repický, M Holeňa ITAT 2018 Proceedings 2203, 72-79, 2018 | 4 | 2018 |
| Investigation of gaussian processes and random forests as surrogate models for evolutionary black-box optimization L Bajer, Z Pitra, M Holeňa Proceedings of the Companion Publication of the 2015 Annual Conference on …, 2015 | 4 | 2015 |
| Combining Gaussian Processes with Neural Networks for Active Learning in Optimization J Ruzicka, J Koza, J Tumpach, Z Pitra, M Holena ECML PKDD 2021: Workshop on Interactive Adaptive Learning, 105-120, 2021 | 2 | 2021 |
| Transfer of Knowledge for Surrogate Model Selection in Cost-Aware Optimization Z Pitra, J Repický, M Holeňa ECML PKDD 2018: Workshop on Interactive Adaptive Learning 2192, 89-94, 2018 | 2 | 2018 |
| Adaptive Selection of Gaussian Process Model for Active Learning in Expensive Optimization J Repický, Z Pitra, M Holena ECML PKDD 2018: Workshop on Interactive Adaptive Learning 2192, 80-84, 2018 | 2 | 2018 |
| Adaptive Generation-Based Evolution Control for Gaussian Process Surrogate Models J Repický, L Bajer, Z Pitra, M Holeňa arXiv preprint arXiv:1709.10443, 2017 | 2 | 2017 |
| Adaptive Doubly Trained Evolution Control for the Covariance Matrix Adaptation Evolution Strategy Z Pitra, L Bajer, J Repický, M Holeňa ITAT 2017 Proceedings 1885, 120-128, 2017 | 2 | 2017 |
Martin HolenaVerified email at cs.cas.cz
