Robust Entropy Search for Safe Efficient Bayesian Optimization

• URL: http://arxiv.org/abs/2405.19059v2
• Date: Fri, 31 May 2024 07:45:53 GMT
• Title: Robust Entropy Search for Safe Efficient Bayesian Optimization
• Authors: Dorina Weichert, Alexander Kister, Sebastian Houben, Patrick Link, Gunar Ernis,
• Abstract summary: We develop an efficient information-based acquisition function that we call Robust Entropy Search (RES) RES reliably finds robust optima, outperforming state-of-the-art algorithms.
• Score: 40.56709991743249
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: The practical use of Bayesian Optimization (BO) in engineering applications imposes special requirements: high sampling efficiency on the one hand and finding a robust solution on the other hand. We address the case of adversarial robustness, where all parameters are controllable during the optimization process, but a subset of them is uncontrollable or even adversely perturbed at the time of application. To this end, we develop an efficient information-based acquisition function that we call Robust Entropy Search (RES). We empirically demonstrate its benefits in experiments on synthetic and real-life data. The results showthat RES reliably finds robust optima, outperforming state-of-the-art algorithms.

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