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arXiv · 2312.12633

Long-run Behaviour of Multi-fidelity Bayesian Optimisation

Gbetondji J-S Dovonon·Jakob Zeitler
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Abstract

Multi-fidelity Bayesian Optimisation (MFBO) has been shown to generally converge faster than single-fidelity Bayesian Optimisation (SFBO) (Poloczek et al. (2017)). Inspired by recent benchmark papers, we are investigating the long-run behaviour of MFBO, based on observations in the literature that it might under-perform in certain scenarios (Mikkola et al. (2023), Eggensperger et al. (2021)). An under-performance of MBFO in the long-run could significantly undermine its application to many research tasks, especially when we are not able to identify when the under-performance begins. We create a simple benchmark study, showcase empirical results and discuss scenarios and possible reasons of under-performance.

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Gbetondji J-S Dovonon, Jakob Zeitler. 2023-12-19. Long-run Behaviour of Multi-fidelity Bayesian Optimisation. https://arxiv.org/abs/2312.12633

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