Choosing a suitable acquisition function for batch Bayesian optimization: comparison of serial and Monte Carlo approaches
Batch Bayesian optimization is widely used for optimizing expensive experimental processes when several samples can be tested together to save time or cost.
Authors
- Julia W. P. Hsu (ORCID: https://orcid.org/0000-0002-7821-3001)
- Weijie Xu (ORCID: https://orcid.org/0000-0002-4198-7265)
- William G. Vandenberghe (ORCID: https://orcid.org/0000-0002-6717-5046)
- Seongkwan Mark Lee (ORCID: https://orcid.org/0000-0002-7240-013X)
- Imon Mia
Institutions
- The University of Texas at Dallas (US)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00066a
- Citations
- 2
- Primary Topic
- Advanced Statistical Process Monitoring
- Type
- article
- Field-Weighted Citation Impact
- 2.80
Funders
- National Science Foundation
- Department of Mechanical Engineering, University of Texas at Austin
- Division of Civil, Mechanical and Manufacturing Innovation