| Expected improvement versus predicted value in surrogate-based optimization F Rehbach, M Zaefferer, B Naujoks, T Bartz-Beielstein Proceedings of the 2020 genetic and evolutionary computation conference, 868-876, 2020 | 27 | 2020 |
| Comparison of parallel surrogate-assisted optimization approaches F Rehbach, M Zaefferer, J Stork, T Bartz-Beielstein Proceedings of the Genetic and Evolutionary Computation Conference, 1348-1355, 2018 | 17 | 2018 |
| In a Nutshell--The Sequential Parameter Optimization Toolbox T Bartz-Beielstein, M Zaefferer, F Rehbach arXiv preprint arXiv:1712.04076, 2017 | 9 | 2017 |
| A novel dynamic multi-criteria ensemble selection mechanism applied to drinking water quality anomaly detection VHA Ribeiro, S Moritz, F Rehbach, G Reynoso-Meza Science of The Total Environment 749, 142368, 2020 | 7 | 2020 |
| Hospital capacity planning using discrete event simulation under special consideration of the COVID-19 pandemic T Bartz-Beielstein, F Rehbach, O Mersmann, E Bartz arXiv preprint arXiv:2012.07188, 2020 | 7 | 2020 |
| GECCO 2018 Industrial Challenge: Monitoring of drinking-water quality F Rehbach, S Moritz, S Chandrasekaran, M Rebolledo, M Friese, ... Accessed: Feb 19, 2019, 2018 | 6 | 2018 |
| Continuous optimization benchmarks by simulation M Zaefferer, F Rehbach International Conference on Parallel Problem Solving from Nature, 273-286, 2020 | 4 | 2020 |
| Variable reduction for surrogate-based optimization F Rehbach, L Gentile, T Bartz-Beielstein Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020 | 4 | 2020 |
| Surrogate-assisted learning of neural networks J Stork, M Zaefferer, A Fischbach, F Rehbach, T Bartz-Beielstein | 4 | 2017 |
| Optimization of High-dimensional Simulation Models Using Synthetic Data T Bartz-Beielstein, E Bartz, F Rehbach, O Mersmann arXiv preprint arXiv:2009.02781, 2020 | 3 | 2020 |
| Parallelized bayesian optimization for expensive robot controller evolution M Rebolledo, F Rehbach, AE Eiben, T Bartz-Beielstein International Conference on Parallel Problem Solving from Nature, 243-256, 2020 | 3 | 2020 |
| Optimization and Adaptation of a Resource Planning Tool for Hospitals Under Special Consideration of the COVID-19 Pandemic T Bartz-Beielstein, M Dröscher, A Gür, A Hinterleitner, T Lawton, ... 2021 IEEE Congress on Evolutionary Computation (CEC), 728-735, 2021 | 2 | 2021 |
| Parallelized Bayesian optimization for problems with expensive evaluation functions M Rebolledo, F Rehbach, AE Eiben, T Bartz-Beielstein Proceedings of the 2020 Genetic and Evolutionary Computation Conference …, 2020 | 2 | 2020 |
| Feature selection for surrogate model-based optimization F Rehbach, L Gentile, T Bartz-Beielstein Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2019 | 2 | 2019 |
| Package ‘SPOT’ T Bartz-Beielstein, M Zaefferer, F Rehbach, M Rebolledo | 1 | 2022 |
| Resource planning for hospitals under special consideration of the COVID-19 pandemic: optimization and sensitivity analysis T Bartz-Beielstein, M Dröscher, A Gür, A Hinterleitner, O Mersmann, ... Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 1 | 2021 |
| Benchmark-Driven Configuration of a Parallel Model-Based Optimization Algorithm F Rehbach, M Zaefferer, A Fischbach, G Rudolph, T Bartz-Beielstein IEEE Transactions on Evolutionary Computation, 2022 | | 2022 |
| Benchmark-Driven Algorithm Configuration Applied to Parallel Model-Based Optimization F Rehbach, M Zaefferer, A Fischbach, G Rudolph, T Bartz-Beielstein TechRxiv, 2022 | | 2022 |
| Surrogate Model Based Hyperparameter Tuning for Deep Learning with SPOT T Bartz-Beielstein, F Rehbach, A Sen, M Zaefferer arXiv preprint arXiv:2105.14625, 2021 | | 2021 |
| Tuning Algorithms for Stochastic Black-Box Optimization: State of the Art and Future Perspectives T Bartz-Beielstein, F Rehbach, M Rebolledo Black Box Optimization, Machine Learning, and No-Free Lunch Theorems, 67-108, 2021 | | 2021 |
