Diederick Vermetten

Orcid: 0000-0003-3040-7162

Affiliations:

Leiden University, The Netherlands

According to our database¹, Diederick Vermetten authored at least 73 papers between 2019 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

MA-BBOB - Reproducibility and Additional Data.

[BibT_eX]

[DOI]

Dataset, May, 2024

Benchmarking Dynamic Binary Value Problems with IOHprofiler - Reproducibility files.

[BibT_eX]

[DOI]

Dataset, April, 2024

Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization - Reproducibility Files.

[BibT_eX]

[DOI]

Dataset, April, 2024

Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics - Reproducibility Files.

[BibT_eX]

[DOI]

Dataset, January, 2024

IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics.

[BibT_eX]

[DOI]

Evol. Comput., 2024

The Importance of Being Constrained: Dealing with Infeasible Solutions in Differential Evolution and Beyond.

[BibT_eX]

[DOI]

Anna V. Kononova

Diederick Vermetten

Fabio Caraffini

Madalina-Andreea Mitran

Daniela Zaharie

Evol. Comput., 2024

In-the-loop Hyper-Parameter Optimization for LLM-Based Automated Design of Heuristics.

[BibT_eX]

[DOI]

Niki van Stein

Diederick Vermetten

Thomas Bäck

CoRR, 2024

Using the Empirical Attainment Function for Analyzing Single-objective Black-box Optimization Algorithms.

[BibT_eX]

[DOI]

CoRR, 2024

Impact of spatial transformations on landscape features of CEC2022 basic benchmark problems.

[BibT_eX]

[DOI]

CoRR, 2024

Explainable Benchmarking for Iterative Optimization Heuristics.

[BibT_eX]

[DOI]

CoRR, 2024

Empirical Analysis of the Dynamic Binary Value Problem with IOHprofiler.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Avoiding Redundant Restarts in Multimodal Global Optimization.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature - PPSN XVIII, 2024

Impact of Spatial Transformations on Exploratory and Deep-Learning Based Landscape Features of CEC2022 Benchmark Suite.

[BibT_eX]

[DOI]

Proceedings of the 16th International Joint Conference on Computational Intelligence, 2024

Sampling in CMA-ES: Low Numbers of Low Discrepancy Points.

[BibT_eX]

[DOI]

Proceedings of the 16th International Joint Conference on Computational Intelligence, 2024

Large-Scale Benchmarking of Metaphor-Based Optimization Heuristics.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Transfer Learning of Surrogate Models via Domain Affine Transformation.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

A Critical Analysis of Raven Roost Optimization.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2024

Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2024

Quantifying Individual and Joint Module Impact in Modular Optimization Frameworks.

[BibT_eX]

[DOI]

Proceedings of the IEEE Congress on Evolutionary Computation, 2024

2023

OPTION: OPTImization Algorithm Benchmarking ONtology.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., December, 2023

MA-BBOB - Reproducibility and Additional Data.

[BibT_eX]

[DOI]

Dataset, December, 2023

Challenges of ELA-based Function Evolution using Genetic Programming - Reproducability files.

[BibT_eX]

[DOI]

Dataset, May, 2023

Using Affine Combinations of BBOB Problems for Performance Assessment - Code and Data.

[BibT_eX]

[DOI]

Diederick Vermetten

Furong Ye

Carola Doerr

Dataset, February, 2023

Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms - Code and Data.

[BibT_eX]

[DOI]

Dataset, February, 2023

Evolutionary Algorithms for Parameter Optimization - Thirty Years Later.

[BibT_eX]

[DOI]

Evol. Comput., 2023

Synergizing Theory and Practice of Automated Algorithm Design for Optimization (Dagstuhl Seminar 23332).

[BibT_eX]

[DOI]

Dagstuhl Reports, 2023

MA-BBOB: A Problem Generator for Black-Box Optimization Using Affine Combinations and Shifts.

[BibT_eX]

[DOI]

CoRR, 2023

Challenges of ELA-Guided Function Evolution Using Genetic Programming.

[BibT_eX]

[DOI]

Proceedings of the 15th International Joint Conference on Computational Intelligence, 2023

Using Affine Combinations of BBOB Problems for Performance Assessment.

[BibT_eX]

[DOI]

Diederick Vermetten

Furong Ye

Carola Doerr

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Modular Differential Evolution.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

Deep BIAS: Detecting Structural Bias using Explainable AI.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Assessing the Generalizability of a Performance Predictive Model.

[BibT_eX]

[DOI]

Andries Petrus Engelbrecht

Carola Doerr

Peter Korosec

Tome Eftimov

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Comparing Algorithm Selection Approaches on Black-Box Optimization Problems.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Towards a General Boolean Function Benchmark Suite.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Benchmarking and analyzing iterative optimization heuristics with IOHprofiler.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the Conference on Genetic and Evolutionary Computation, 2023

Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2023

General Boolean Function Benchmark Suite.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the Applications of Evolutionary Computation - 26th European Conference, 2023

BBOB Instance Analysis: Landscape Properties and Algorithm Performance Across Problem Instances.

[BibT_eX]

[DOI]

Proceedings of the Applications of Evolutionary Computation - 26th European Conference, 2023

Using Knowledge Graphs for Performance Prediction of Modular Optimization Algorithms.

[BibT_eX]

[DOI]

Proceedings of the Applications of Evolutionary Computation - 26th European Conference, 2023

Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Automated Machine Learning, 2023

PS-AAS: Portfolio Selection for Automated Algorithm Selection in Black-Box Optimization.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Automated Machine Learning, 2023

2022

To Switch or not to Switch: Predicting the Benefit of Switching between Algorithms based on Trajectory Features - Dataset.

[BibT_eX]

[DOI]

Dataset, October, 2022

Data Sets for the study "Non-Elitist Selection Can Improve the Performance of Irace".

[BibT_eX]

[DOI]

Dataset, April, 2022

Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data.

[BibT_eX]

[DOI]

Dataset, April, 2022

Linking Problem Landscape Features with the Performance of Individual CMA-ES Modules - Data.

[BibT_eX]

[DOI]

Dataset, February, 2022

Analyzing the Impact of Undersampling on the Benchmarkingand Configuration of Evolutionary Algorithms - Dataset.

[BibT_eX]

[DOI]

Dataset, January, 2022

IOHanalyzer: Detailed Performance Analyses for Iterative Optimization Heuristics.

[BibT_eX]

[DOI]

ACM Trans. Evol. Learn. Optim., 2022

BIAS: A Toolbox for Benchmarking Structural Bias in the Continuous Domain.

[BibT_eX]

[DOI]

IEEE Trans. Evol. Comput., 2022

Chaining of Numerical Black-box Algorithms: Warm-Starting and Switching Points.

[BibT_eX]

[DOI]

CoRR, 2022

Non-Elitist Selection among Survivor Configurations can Improve the Performance of Irace.

[BibT_eX]

[DOI]

Furong Ye

Diederick L. Vermetten

Carola Doerr

Thomas Bäck

CoRR, 2022

Non-elitist Selection Can Improve the Performance of Irace.

[BibT_eX]

[DOI]

Proceedings of the Parallel Problem Solving from Nature - PPSN XVII, 2022

Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

Using structural bias to analyse the behaviour of modular CMA-ES.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Boston, Massachusetts, USA, July 9, 2022

Benchmarking and analyzing iterative optimization heuristics with IOH profiler.

[BibT_eX]

[DOI]

Proceedings of the GECCO '22: Genetic and Evolutionary Computation Conference, Companion Volume, Boston, Massachusetts, USA, July 9, 2022

Trajectory-based Algorithm Selection with Warm-starting.

[BibT_eX]

[DOI]

Proceedings of the IEEE Congress on Evolutionary Computation, 2022

2021

IOHanalyzer version 0.1.6.1 + example datasets.

[BibT_eX]

[DOI]

Dataset, October, 2021

Benchmarking the Status of Default Pseudorandom Number Generators in Common Programming Languages.

[BibT_eX]

[DOI]

Nils van den Honert

Diederick Vermetten

Anna V. Kononova

CoRR, 2021

Is there anisotropy in structural bias?

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

Proceedings of the GECCO '21: Genetic and Evolutionary Computation Conference, 2021

2020

Squirrel: A Switching Hyperparameter Optimizer.

[BibT_eX]

[DOI]

Katharina Eggensperger

CoRR, 2020

IOHanalyzer: Performance Analysis for Iterative Optimization Heuristic.

[BibT_eX]

[DOI]

CoRR, 2020

Integrated vs. sequential approaches for selecting and tuning CMA-ES variants.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

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.

[BibT_eX]

[DOI]

CoRR, 2019

Online selection of CMA-ES variants.

[BibT_eX]

[DOI]

Proceedings of the Genetic and Evolutionary Computation Conference, 2019

Diederick Vermetten

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