Diederick Vermetten
Orcid: 0000-0003-3040-7162Affiliations:
- Leiden University, The Netherlands
According to our database1,
Diederick Vermetten
authored at least 69 papers
between 2019 and 2024.
Collaborative distances:
Collaborative distances:
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on orcid.org
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Bibliography
2024
Dataset, April, 2024
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization - Reproducibility Files.
Dataset, April, 2024
Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics - Reproducibility Files.
Dataset, January, 2024
The Importance of Being Constrained: Dealing with Infeasible Solutions in Differential Evolution and Beyond.
Evol. Comput., 2024
Using the Empirical Attainment Function for Analyzing Single-objective Black-box Optimization Algorithms.
CoRR, 2024
Impact of spatial transformations on landscape features of CEC2022 basic benchmark problems.
CoRR, 2024
Proceedings of the Genetic and Evolutionary Computation Conference, 2024
Proceedings of the Genetic and Evolutionary Computation Conference, 2024
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024
Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024
Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization.
Proceedings of the Genetic and Evolutionary Computation Conference, 2024
Proceedings of the IEEE Congress on Evolutionary Computation, 2024
2023
IEEE Trans. Evol. Comput., December, 2023
Challenges of ELA-based Function Evolution using Genetic Programming - Reproducability files.
Dataset, May, 2023
Using Affine Combinations of BBOB Problems for Performance Assessment - Code and Data.
Dataset, February, 2023
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms - Code and Data.
Dataset, February, 2023
Evol. Comput., 2023
Synergizing Theory and Practice of Automated Algorithm Design for Optimization (Dagstuhl Seminar 23332).
Dagstuhl Reports, 2023
MA-BBOB: A Problem Generator for Black-Box Optimization Using Affine Combinations and Shifts.
CoRR, 2023
Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
Analysis of modular CMA-ES on strict box-constrained problems in the SBOX-COST benchmarking suite.
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems.
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023
Proceedings of the Genetic and Evolutionary Computation Conference, 2023
Proceedings of the 17th ACM/SIGEVO Conference on Foundations of Genetic Algorithms, 2023
To Switch or Not to Switch: Predicting the Benefit of Switching Between Algorithms Based on Trajectory Features.
Proceedings of the Applications of Evolutionary Computation - 26th European Conference, 2023
BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances.
Proceedings of the Applications of Evolutionary Computation - 26th European Conference, 2023
Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms.
Proceedings of the Applications of Evolutionary Computation - 26th European Conference, 2023
Proceedings of the IEEE Congress on Evolutionary Computation, 2023
MA-BBOB: Many-Affine Combinations of BBOB Functions for Evaluating AutoML Approaches in Noiseless Numerical Black-Box Optimization Contexts.
Proceedings of the International Conference on Automated Machine Learning, 2023
PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization.
Proceedings of the International Conference on Automated Machine Learning, 2023
2022
Data Sets for the study "Non-Elitist Selection Can Improve the Performance of Irace".
Dataset, April, 2022
Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data.
Dataset, April, 2022
Linking Problem Landscape Features with the Performance of Individual CMA-ES Modules - Data.
Dataset, February, 2022
Analyzing the Impact of Undersampling on the Benchmarkingand Configuration of Evolutionary Algorithms - Dataset.
Dataset, January, 2022
ACM Trans. Evol. Learn. Optim., 2022
IEEE Trans. Evol. Comput., 2022
CoRR, 2022
Non-Elitist Selection among Survivor Configurations can Improve the Performance of Irace.
CoRR, 2022
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022
Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022
IOHanalyzer: Detailed performance analyses for iterative optimization heuristics: hot-off-the-press track @ GECCO 2022.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
Analyzing the impact of undersampling on the benchmarking and configuration of evolutionary algorithms.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
The importance of landscape features for performance prediction of modular CMA-ES variants.
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022
Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022
Proceedings of the IEEE Congress on Evolutionary Computation, 2022
2021
CoRR, 2021
Benchmarking the Status of Default Pseudorandom Number Generators in Common Programming Languages.
CoRR, 2021
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules.
Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021
2020
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020
Towards dynamic algorithm selection for numerical black-box optimization: investigating BBOB as a use case.
Proceedings of the GECCO '20: Genetic and Evolutionary Computation Conference, 2020
2019
Sequential vs. Integrated Algorithm Selection and Configuration: A Case Study for the Modular CMA-ES.
CoRR, 2019
Proceedings of the Genetic and Evolutionary Computation Conference, 2019