Online selection of CMA-ES variants D Vermetten, S van Rijn, T Bäck, C Doerr Proceedings of the Genetic and Evolutionary Computation Conference, 951-959, 2019 | 23 | 2019 |
IOHanalyzer: Detailed performance analyses for iterative optimization heuristics H Wang, D Vermetten, F Ye, C Doerr, T Bäck ACM Transactions on Evolutionary Learning and Optimization 2 (1), 1-29, 2022 | 21 | 2022 |
Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules J de Nobel, D Vermetten, H Wang, C Doerr, T Bäck Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 14 | 2021 |
Performance comparison of optimization methods on variational quantum algorithms X Bonet-Monroig, H Wang, D Vermetten, B Senjean, C Moussa, T Bäck, ... arXiv preprint arXiv:2111.13454, 2021 | 13 | 2021 |
Integrated vs. sequential approaches for selecting and tuning CMA-ES variants D Vermetten, H Wang, C Doerr, T Back ACM Genetic and Evolutionary Computation Conference (GECCO'20), 2020 | 11 | 2020 |
Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case D Vermetten, H Wang, T Bäck, C Doerr Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 654-662, 2020 | 9 | 2020 |
Is there anisotropy in structural bias? D Vermetten, AV Kononova, F Caraffini, H Wang, T Bäck Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 7 | 2021 |
IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic. CoRR abs/2007.03953 (2020) H Wang, D Vermetten, F Ye, C Doerr, T Bäck arXiv preprint arXiv:2007.03953, 2020 | 5 | 2020 |
Analysis of structural bias in differential evolution configurations D Vermetten, B van Stein, AV Kononova, F Caraffini Differential Evolution: From Theory to Practice, 1-22, 2022 | 4 | 2022 |
OPTION: optimization algorithm benchmarking ontology A Kostovska, D Vermetten, C Doerr, S Džeroski, P Panov, T Eftimov Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2021 | 4 | 2021 |
Per-run algorithm selection with warm-starting using trajectory-based features A Kostovska, A Jankovic, D Vermetten, J de Nobel, H Wang, T Eftimov, ... Parallel Problem Solving from Nature–PPSN XVII: 17th International …, 2022 | 3 | 2022 |
BIAS: a toolbox for benchmarking structural bias in the continuous domain D Vermetten, B van Stein, F Caraffini, LL Minku, AV Kononova IEEE Transactions on Evolutionary Computation 26 (6), 1380-1393, 2022 | 3 | 2022 |
Squirrel: A switching hyperparameter optimizer N Awad, G Shala, D Deng, N Mallik, M Feurer, K Eggensperger, ... arXiv preprint arXiv:2012.08180, 2020 | 3 | 2020 |
Trajectory-based algorithm selection with warm-starting A Jankovic, D Vermetten, A Kostovska, J de Nobel, T Eftimov, C Doerr 2022 IEEE Congress on Evolutionary Computation (CEC), 1-8, 2022 | 2 | 2022 |
The importance of landscape features for performance prediction of modular CMA-ES variants A Kostovska, D Vermetten, S Džeroski, C Doerr, P Korosec, T Eftimov Proceedings of the Genetic and Evolutionary Computation Conference, 648-656, 2022 | 2 | 2022 |
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics J de Nobel, F Ye, D Vermetten, H Wang, C Doerr, T Bäck arXiv preprint arXiv:2111.04077, 2021 | 2 | 2021 |
Using structural bias to analyse the behaviour of modular CMA-ES D Vermetten, F Caraffini, B van Stein, AV Kononova Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022 | 1 | 2022 |
Chaining of numerical black-box algorithms: warm-starting and switching points D Schröder, D Vermetten, H Wang, C Doerr, T Bäck arXiv preprint arXiv:2204.06539, 2022 | 1 | 2022 |
Sequential vs. integrated algorithm selection and configuration: A case study for the modular cma-es D Vermetten, H Wang, C Doerr, T Bäck arXiv preprint arXiv:1912.05899, 2019 | 1 | 2019 |
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms A Kostovska, D Vermetten, S Džeroski, P Panov, T Eftimov, C Doerr arXiv preprint arXiv:2301.09876, 2023 | | 2023 |