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Steven Adriaensen
Steven Adriaensen
Postdoctoral Researcher, Albert-Ludwigs-Universität Freiburg
在 informatik.uni-freiburg.de 的电子邮件经过验证 - 首页
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引用次数
引用次数
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Metaheuristics “in the large”
J Swan, S Adriaensen, AEI Brownlee, K Hammond, CG Johnson, A Kheiri, ...
European Journal of Operational Research 297 (2), 393-406, 2022
852022
A research agenda for metaheuristic standardization
J Swan, S Adriaensen, M Bishr, EK Burke, JA Clark, P De Causmaecker, ...
Proceedings of the XI metaheuristics international conference, 1-3, 2015
552015
Learning step-size adaptation in CMA-ES
G Shala, A Biedenkapp, N Awad, S Adriaensen, M Lindauer, F Hutter
Parallel Problem Solving from Nature–PPSN XVI: 16th International Conference …, 2020
362020
Fair-share ILS: a simple state-of-the-art iterated local search hyperheuristic
S Adriaensen, T Brys, A Nowé
Proceedings of the 2014 annual conference on genetic and evolutionary …, 2014
342014
Automated dynamic algorithm configuration
S Adriaensen, A Biedenkapp, G Shala, N Awad, T Eimer, M Lindauer, ...
Journal of Artificial Intelligence Research 75, 1633-1699, 2022
312022
A benchmark set extension and comparative study for the hyflex framework
S Adriaensen, G Ochoa, A Nowé
2015 IEEE Congress on Evolutionary Computation (CEC), 784-791, 2015
302015
DACBench: A benchmark library for dynamic algorithm configuration
T Eimer, A Biedenkapp, M Reimer, S Adriaensen, F Hutter, M Lindauer
Proceedings of the Thirtieth International Joint Conference on Artificial …, 2021
202021
Designing reusable metaheuristic methods: A semi-automated approach
S Adriaensen, T Brys, A Nowé
2014 IEEE Congress on Evolutionary Computation (CEC), 2969-2976, 2014
182014
Towards a White Box Approach to Automated Algorithm Design.
S Adriaensen, A Nowé
IJCAI, 554-560, 2016
162016
Case study: An analysis of accidental complexity in a state-of-the-art hyper-heuristic for HyFlex
S Adriaensen, A Nowé
2016 IEEE Congress on Evolutionary Computation (CEC), 1485-1492, 2016
152016
Efficient Bayesian Learning Curve Extrapolation using Prior-Data Fitted Networks
S Adriaensen, H Rakotoarison, S Müller, F Hutter
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS …, 2023
132023
Extending the “open-closed principle” to automated algorithm configuration
J Swan, S Adriænsen, AD Barwell, K Hammond, DR White
Evolutionary computation 27 (1), 173-193, 2019
52019
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
H Rakotoarison, S Adriaensen, N Mallik, S Garibov, E Bergman, F Hutter
arXiv preprint arXiv:2404.16795, 2024
22024
An importance sampling approach to the estimation of algorithm performance in automated algorithm design
S Adriaensen, F Moons, A Nowé
Learning and Intelligent Optimization: 11th International Conference, LION …, 2017
22017
On the Semi-automated Design of Reusable Heuristics
S Adriaensen
Vrije Universiteit Brussel, 2018
12018
On Task Scheduling Policies for Work-Stealing Schedulers
S Adriaensen, Y Fathy, A Nowé
Proceedings of the Multidisciplinary International Conference on Scheduling …, 2015
2015
NOSBench-101: Towards Reproducible Neural Optimizer Search
G Karakasli, S Adriaensen, F Hutter
AutoML Conference 2024 (Workshop Track), 0
From Epoch to Sample Size: Developing New Data-driven Priors for Learning Curve Prior-Fitted Networks
TJ Viering, S Adriaensen, H Rakotoarison, F Hutter
AutoML Conference 2024 (Workshop Track), 0
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