ORCID Profile
0000-0002-9001-1146
Current Organisation
Deakin University
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Publisher: IEEE
Date: 03-2016
Publisher: Elsevier BV
Date: 05-2020
Publisher: International Joint Conferences on Artificial Intelligence Organization
Date: 07-2020
Abstract: In order to improve the performance of Bayesian optimisation, we develop a modified Gaussian process upper confidence bound (GP-UCB) acquisition function. This is done by s ling the exploration-exploitation trade-off parameter from a distribution. We prove that this allows the expected trade-off parameter to be altered to better suit the problem without compromising a bound on the function's Bayesian regret. We also provide results showing that our method achieves better performance than GP-UCB in a range of real-world and synthetic problems.
Publisher: Springer International Publishing
Date: 2019
Publisher: ACM
Date: 15-10-2016
Publisher: IEEE
Date: 08-2016
Publisher: Elsevier BV
Date: 2015
Publisher: Elsevier BV
Date: 09-2022
Location: Australia
No related grants have been discovered for Julian Berk.