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Jacob de Nobel
Jacob de Nobel
PhD. Candidate, Leiden University
Verified email at liacs.leidenuniv.nl
Title
Cited by
Cited by
Year
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
332021
Per-run algorithm selection with warm-starting using trajectory-based features
A Kostovska, A Jankovic, D Vermetten, J de Nobel, H Wang, T Eftimov, ...
International Conference on Parallel Problem Solving from Nature, 46-60, 2022
292022
Iohexperimenter: Benchmarking platform for iterative optimization heuristics
J de Nobel, F Ye, D Vermetten, H Wang, C Doerr, T Bäck
Evolutionary Computation, 1-6, 2024
202024
Combining supervised and unsupervised machine learning methods for phenotypic functional genomics screening
WA Omta, RG van Heesbeen, I Shen, J de Nobel, D Robers, ...
SLAS DISCOVERY: Advancing the Science of Drug Discovery 25 (6), 655-664, 2020
152020
Evolutionary algorithms for parameter optimization—thirty years later
THW Bäck, AV Kononova, B van Stein, H Wang, KA Antonov, ...
Evolutionary Computation 31 (2), 81-122, 2023
122023
Explorative data analysis of time series based algorithm features of CMA-ES variants
J de Nobel, H Wang, T Baeck
Proceedings of the Genetic and Evolutionary Computation Conference, 510-518, 2021
82021
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. CoRR abs/2111.04077 (2021)
J de Nobel, F Ye, D Vermetten, H Wang, C Doerr, T Bäck
arXiv preprint arXiv:2111.04077, 2021
72021
Improving comprehension efficiency of high content screening data through interactive visualizations
WA Omta, J Nobel, J Klumperman, DA Egan, MR Spruit, MJS Brinkhuis
Assay and drug development technologies 15 (6), 247-256, 2017
62017
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
42022
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems
A Thomaser, J De Nobel, D Vermetten, F Ye, T Bäck, A Kononova
Proceedings of the Genetic and Evolutionary Computation Conference, 856-863, 2023
22023
Optimizing stimulus energy for cochlear implants with a machine learning model of the auditory nerve
J de Nobel, AV Kononova, JJ Briaire, JHM Frijns, THW Bäck
Hearing Research 432, 108741, 2023
22023
Solving Deep Reinforcement Learning Benchmarks with Linear Policy Networks
A Wong, J de Nobel, T Bäck, A Plaat, AV Kononova
arXiv preprint arXiv:2402.06912, 2024
2024
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms
F Clément, D Vermetten, J De Nobel, AD Jesus, L Paquete, C Doerr
Proceedings of the Genetic and Evolutionary Computation Conference, 1330-1338, 2023
2023
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler
F Neumann, A Neumann, C Qian, AV Do, J de Nobel, D Vermetten, ...
2023 IEEE Congress on Evolutionary Computation (CEC), 1-9, 2023
2023
What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms
F Ye, F Neumann, J de Nobel, A Neumann, T Bäck
arXiv preprint arXiv:2303.04611, 2023
2023
Benchmarking and analyzing iterative optimization heuristics with IOH profiler
C Doerr, H Wang, D Vermetten, T Bäck, J De Nobel, F Ye
Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2022
2022
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features
D Vermetten, J de Nobel, C Doerr
arXiv preprint arXiv:2204.09483, 2022
2022
Results from the Joint Nevergrad and IOHprofiler Open Optimization Competition
T Bäck, P Bennet, J de Nobel, C Doerr, J Dreo, H Rakotoarison, J Rapin, ...
2021
IOHProfiler
C Doerr, H Wang, D Vermetten, T Bäck, J de Nobel, F Ye
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Articles 1–19