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Jacob de Nobel
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2020 – today
- 2024
- [j2]Jacob de Nobel
, Furong Ye
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. Evol. Comput. 32(3): 205-210 (2024) - [c14]Saba Sadeghi Ahouei
Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. GECCO 2024 - [c13]Carola Doerr
Benchmarking and Analyzing Iterative Optimization Heuristics with IOHprofiler. GECCO Companion 2024: 791-799 - [c12]Furong Ye
What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms. GECCO 2024 - [c11]Jacob de Nobel, Diederick Vermetten, Thomas H. W. Bäck, Anna V. Kononova:
Sampling in CMA-ES: Low Numbers of Low Discrepancy Points. IJCCI 2024: 120-126 - [c10]Jacob de Nobel
Avoiding Redundant Restarts in Multimodal Global Optimization. PPSN (2) 2024: 268-283 - [i14]Annie Wong, Jacob de Nobel, Thomas Bäck, Aske Plaat, Anna V. Kononova:
Solving Deep Reinforcement Learning Benchmarks with Linear Policy Networks. CoRR abs/2402.06912 (2024) - [i13]Jacob de Nobel, Diederick Vermetten, Anna V. Kononova, Ofer M. Shir, Thomas Bäck:
Avoiding Redundant Restarts in Multimodal Global Optimization. CoRR abs/2405.01226 (2024) - [i12]Saba Sadeghi Ahouei, Jacob de Nobel, Aneta Neumann, Thomas Bäck, Frank Neumann:
Evolving Reliable Differentiating Constraints for the Chance-constrained Maximum Coverage Problem. CoRR abs/2405.18772 (2024) - [i11]Jacob de Nobel, Diederick Vermetten, Thomas H. W. Bäck, Anna V. Kononova:
Sampling in CMA-ES: Low Numbers of Low Discrepancy Points. CoRR abs/2409.15941 (2024) - 2023
- [j1]Thomas H. W. Bäck
Evolutionary Algorithms for Parameter Optimization - Thirty Years Later. Evol. Comput. 31(2): 81-122 (2023) - [c9]Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CEC 2023: 1-9 - [c8]André Thomaser
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems. GECCO 2023: 856-863 - [c7]Carola Doerr
Benchmarking and analyzing iterative optimization heuristics with IOHprofiler. GECCO Companion 2023: 938-945 - [c6]François Clément
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms. GECCO 2023: 1330-1338 - [d2]François Clément
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms - Code and Data. Zenodo, 2023 - [i10]Frank Neumann, Aneta Neumann, Chao Qian, Anh Viet Do, Jacob de Nobel, Diederick Vermetten, Saba Sadeghi Ahouei, Furong Ye, Hao Wang, Thomas Bäck:
Benchmarking Algorithms for Submodular Optimization Problems Using IOHProfiler. CoRR abs/2302.01464 (2023) - [i9]Furong Ye, Frank Neumann, Jacob de Nobel, Aneta Neumann, Thomas Bäck:
What Performance Indicators to Use for Self-Adaptation in Multi-Objective Evolutionary Algorithms. CoRR abs/2303.04611 (2023) - [i8]André Thomaser, Jacob de Nobel, Diederick Vermetten, Furong Ye, Thomas Bäck, Anna V. Kononova:
When to be Discrete: Analyzing Algorithm Performance on Discretized Continuous Problems. CoRR abs/2304.13117 (2023) - [i7]François Clément, Diederick Vermetten, Jacob de Nobel, Alexandre D. Jesus, Luís Paquete, Carola Doerr:
Computing Star Discrepancies with Numerical Black-Box Optimization Algorithms. CoRR abs/2306.16998 (2023) - 2022
- [c5]Anja Jankovic, Diederick Vermetten
Trajectory-based Algorithm Selection with Warm-starting. CEC 2022: 1-8 - [c4]Carola Doerr, Hao Wang, Diederick Vermetten, Thomas Bäck, Jacob de Nobel, Furong Ye:
Benchmarking and analyzing iterative optimization heuristics with IOH profiler. GECCO Companion 2022: 1334-1341 - [c3]Ana Kostovska
Per-run Algorithm Selection with Warm-Starting Using Trajectory-Based Features. PPSN (1) 2022: 46-60 - [d1]Anja Jankovic
Per-Run Algorithm Selection with Warm-starting using Trajectory-based Features - Data. Zenodo, 2022 - [i6]Anja Jankovic, Diederick Vermetten, Ana Kostovska, Jacob de Nobel, Tome Eftimov, Carola Doerr:
Trajectory-based Algorithm Selection with Warm-starting. CoRR abs/2204.06397 (2022) - [i5]Ana Kostovska, Anja Jankovic, Diederick Vermetten, Jacob de Nobel, Hao Wang, Tome Eftimov, Carola Doerr:
Per-run Algorithm Selection with Warm-starting using Trajectory-based Features. CoRR abs/2204.09483 (2022) - [i4]Jacob de Nobel, Anna V. Kononova, Jeroen Briaire, Johan H. M. Frijns, Thomas Bäck:
Optimizing Stimulus Energy for Cochlear Implants with a Machine Learning Model of the Auditory Nerve. CoRR abs/2211.07285 (2022) - 2021
- [c2]Jacob de Nobel, Hao Wang, Thomas Bäck
Explorative data analysis of time series based algorithm features of CMA-ES variants. GECCO 2021: 510-518 - [c1]Jacob de Nobel, Diederick Vermetten
Tuning as a means of assessing the benefits of new ideas in interplay with existing algorithmic modules. GECCO Companion 2021: 1375-1384 - [i3]Jacob de Nobel, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
Tuning as a Means of Assessing the Benefits of New Ideas in Interplay with Existing Algorithmic Modules. CoRR abs/2102.12905 (2021) - [i2]Jacob de Nobel, Hao Wang, Thomas Bäck:
Explorative Data Analysis of Time Series based AlgorithmFeatures of CMA-ES Variants. CoRR abs/2104.08098 (2021) - [i1]Jacob de Nobel, Furong Ye, Diederick Vermetten, Hao Wang, Carola Doerr, Thomas Bäck:
IOHexperimenter: Benchmarking Platform for Iterative Optimization Heuristics. CoRR abs/2111.04077 (2021)
Coauthor Index
aka: Thomas H. W. Bäck
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