Explorative data analysis of time series based algorithm features of CMA-ES variants. - Jacob de Nobel; Hao Wang 025; Thomas Bäck (GECCO, 2021)

Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules. - Jacob de Nobel; Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (GECCO Companion, 2021)

Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants. - Jacob de Nobel; Hao Wang 025; Thomas Bäck (CoRR, 2021)

Trajectory-based Algorithm Selection with Warm-starting. - Anja Jankovic 001; Diederick Vermetten; Ana Kostovska; Jacob de Nobel; Tome Eftimov; Carola Doerr (CEC, 2022)

Benchmarking and analyzing iterative optimization heuristics with IOH profiler. - Carola Doerr; Hao Wang 025; Diederick Vermetten; Thomas Bäck; Jacob de Nobel; Furong Ye (GECCO Companion, 2022)

Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features. - Ana Kostovska; Anja Jankovic 001; Diederick Vermetten; Jacob de Nobel; Hao Wang 025; Tome Eftimov; Carola Doerr (PPSN (1), 2022)

Optimizing Stimulus Energy for Cochlear Implants with a Machine Learning Model of the Auditory Nerve. - Jacob de Nobel; Anna V. Kononova; Jeroen J. Briaire; Johan H. M. Frijns; Thomas Bäck (CoRR, 2022)

Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data. - Anja Jankovic 001; Ana Kostovska; Diederick Vermetten; Jacob de Nobel; Hao Wang 025; Tome Eftimov; Carola Doerr (Zenodo, 2022)

Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. - Frank Neumann 001; Aneta Neumann; Chao Qian 001; Anh Viet Do; Jacob de Nobel; Diederick Vermetten; Saba Sadeghi Ahouei; Furong Ye; Hao Wang 025; Thomas Bäck (CEC, 2023)

Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms. - François Clément; Diederick Vermetten; Jacob de Nobel; Alexandre D. Jesus; Luís Paquete; Carola Doerr (GECCO, 2023)

Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. - Carola Doerr; Hao Wang 025; Diederick Vermetten; Thomas Bäck; Jacob de Nobel; Furong Ye (GECCO Companion, 2023)

When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems. - André Thomaser; Jacob de Nobel; Diederick Vermetten; Furong Ye; Thomas Bäck; Anna V. Kononova (GECCO, 2023)

Evolutionary Algorithms for Parameter Optimization - Thirty Years Later. - Thomas H. W. Bäck; Anna V. Kononova; Bas van Stein; Hao Wang 025; Kirill A. Antonov; Roman T. Kalkreuth; Jacob de Nobel; Diederick Vermetten; Roy de Winter; Furong Ye (Evol. Comput., 2023)

Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms - Code and Data. - François Clément; Diederick Vermetten; Jacob de Nobel; Alexandre D. Jesus; Luís Paquete; Carola Doerr (Zenodo, 2023)

Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. - Saba Sadeghi Ahouei; Jacob de Nobel; Aneta Neumann; Thomas Bäck; Frank Neumann 001 (GECCO, 2024)

Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler. - Carola Doerr; Diederick Vermetten; Jacob de Nobel; Thomas Bäck (GECCO Companion, 2024)

What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms. - Furong Ye; Frank Neumann 001; Jacob de Nobel; Aneta Neumann; Thomas Bäck (GECCO, 2024)

Sampling in CMA-ES: Low Numbers of Low Discrepancy Points. - Jacob de Nobel; Diederick Vermetten; Thomas H. W. Bäck; Anna V. Kononova (IJCCI, 2024)

Optimizing Causal Interventions in Hybrid Bayesian Networks - A Discretization, Knowledge Compilation, and Heuristic Optimization Approach. - Maarten C. Vonk; Diederick Vermetten; Jacob de Nobel; Sebastiaan Brand; Ninoslav Malekovic; Thomas Bäck; Alfons Laarman; Anna V. Kononova (IPMU (1), 2024)

Avoiding Redundant Restarts in Multimodal Global Optimization. - Jacob de Nobel; Diederick Vermetten; Anna V. Kononova; Ofer M. Shir; Thomas Bäck (PPSN (2), 2024)

Solving Deep Reinforcement Learning Benchmarks with Linear Policy Networks. - Annie Wong; Jacob de Nobel; Thomas Bäck; Aske Plaat; Anna V. Kononova (CoRR, 2024)

MO-IOHinspector: Anytime Benchmarking of Multi-Objective Algorithms using IOHprofiler. - Diederick Vermetten; Jeroen Rook; Oliver Ludger Preuß; Jacob de Nobel; Carola Doerr; Manuel López-Ibáñez 001; Heike Trautmann; Thomas Bäck (CoRR, 2024)

IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. - Jacob de Nobel; Furong Ye; Diederick Vermetten; Hao Wang 025; Carola Doerr; Thomas Bäck (Evol. Comput., 2024)

Sampling in CMA-ES: Low Numbers of Low Discrepancy Points. - Jacob de Nobel; Diederick Vermetten; Anna V. Kononova; Thomas Bäck (Zenodo, 2024)

MO-IOHinspector: Anytime Benchmarking of Multi-objective Algorithms Using IOHprofiler. - Diederick Vermetten; Jeroen Rook; Oliver L. Preuß; Jacob de Nobel; Carola Doerr; Manuel López-Ibáñez 001; Heike Trautmann; Thomas Bäck (EMO (1), 2025)

Abnormal Mutations: Evolution Strategies Don't Require Gaussianity. - Jacob de Nobel; Diederick Vermetten; Hao Wang 025; Anna V. Kononova; Günter Rudolph; Thomas Bäck (GECCO, 2025)

From Spikes to Speech: NeuroVoc - A Biologically Plausible Vocoder Framework for Auditory Perception and Cochlear Implant Simulation. - Jacob de Nobel; Jeroen J. Briaire; Thomas H. W. Bäck; Anna V. Kononova; Johan H. M. Frijns (CoRR, 2025)