Multi-Agent Collaborative Bayesian Optimization via Constrained Gaussian Processes

Author:

Chen Qiyuan1,Jiang Liangkui2,Qin Hantang2ORCID,Kontar Raed Al1ORCID

Affiliation:

1. University of Michigan, Ann Arbor, MI

2. University of Wisconsin, Madison, WI

Publisher

Informa UK Limited

Reference33 articles.

1. Closed-loop optimization of fast-charging protocols for batteries with machine learning

2. “Batch Bayesian Optimization via Simulation Matching,” in;Azimi J.;Advances in Neural Information Processing Systems,2010

3. Bai T. Li Y. Shen Y. Zhang X. Zhang W. and Cui B. (2023) “Transfer Learning for Bayesian Optimization: A Survey ” arXiv preprint arXiv:2302.05927.

4. “Botorch: A Framework for Efficient Monte-Carlo Bayesian Optimization,”;Balandat M.;in Advances in Neural Information Processing Systems,2020

5. Chowdhury, S. R., and Gopalan, A. (2017), “On Kernelized Multi-Armed Bandits,” in International Conference on Machine Learning, pp. 844–853, PMLR.

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