MBORE

Author:

De Ath George1ORCID,Chugh Tinkle1ORCID,Rahat Alma A. M.2ORCID

Affiliation:

1. University of Exeter, Exeter, United Kingdom

2. Swansea University, Swansea, United Kingdom

Funder

EPSRC

Publisher

ACM

Reference90 articles.

1. BoTorch: A Framework for Efficient Monte-Carlo Bayesian Optimization;Balandat Maximilian;Advances in Neural Information Processing Systems,2020

2. Syrine Belakaria , Aryan Deshwal , and Janardhan Rao Doppa . 2019 . Max-value Entropy Search for Multi-Objective Bayesian Optimization . In Advances in Neural Information Processing Systems , Vol. 32 . Curran Associates, Inc., 7825--7835. Syrine Belakaria, Aryan Deshwal, and Janardhan Rao Doppa. 2019. Max-value Entropy Search for Multi-Objective Bayesian Optimization. In Advances in Neural Information Processing Systems, Vol. 32. Curran Associates, Inc., 7825--7835.

3. James Bergstra , Rémi Bardenet , Yoshua Bengio , and Balázs Kégl . 2011 . Algorithms for Hyper-Parameter Optimization . In Advances in Neural Information Processing Systems , Vol. 24 . Curran Associates, Inc., 281--305. James Bergstra, Rémi Bardenet, Yoshua Bengio, and Balázs Kégl. 2011. Algorithms for Hyper-Parameter Optimization. In Advances in Neural Information Processing Systems, Vol. 24. Curran Associates, Inc., 281--305.

4. Discriminative learning for differing training and test distributions

5. A parallel global multiobjective framework for optimization: pagmo

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Mono-surrogate vs multi-surrogate in multi-objective bayesian optimisation;Proceedings of the Genetic and Evolutionary Computation Conference Companion;2022-07-09

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