• Corpus ID: 235377013

EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions

@article{Bliek2021EXPObenchBS,
  title={EXPObench: Benchmarking Surrogate-based Optimisation Algorithms on Expensive Black-box Functions},
  author={Laurens Bliek and Arthur Guijt and Rickard Karlsson and Sicco Verwer and Mathijs de Weerdt},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.04618}
}
Surrogate algorithms such as Bayesian optimisation are especially designed for black-box optimisation problems with expensive objectives, such as hyperparameter tuning or simulation-based optimisation. In the literature, these algorithms are usually evaluated with synthetic benchmarks which are well established but have no expensive objective, and only on one or two real-life applications which vary wildly between papers. There is a clear lack of standardisation when it comes to benchmarking… 

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