https://github.com/jiangyan-zhao/epbo
Implementation code for the paper "Bayesian Optimization via Exact Penalty"
https://github.com/jiangyan-zhao/epbo
bayesian-optimization constrained-bayesian-optimization global-optimization gradient-free-optimization
Last synced: 8 months ago
JSON representation
Implementation code for the paper "Bayesian Optimization via Exact Penalty"
- Host: GitHub
- URL: https://github.com/jiangyan-zhao/epbo
- Owner: Jiangyan-Zhao
- License: agpl-3.0
- Created: 2023-04-21T08:21:30.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-02-29T15:18:54.000Z (over 2 years ago)
- Last Synced: 2025-09-04T19:57:36.643Z (10 months ago)
- Topics: bayesian-optimization, constrained-bayesian-optimization, global-optimization, gradient-free-optimization
- Language: R
- Homepage:
- Size: 1.96 MB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: NEWS.md
- License: LICENSE.md
- Citation: CITATION.cff
Awesome Lists containing this project
README
# EPBO: Bayesian Optimization via Exact Penalty
An R package that implements a series of constrained Bayesian optimization algorithms. (**under development**)
Implementation of the EPBO method proposed in
[Jiangyan Zhao & Jin Xu (07 Feb 2024): Bayesian Optimization via Exact Penalty, Technometrics, DOI: 10.1080/00401706.2024.2315937](https://www.tandfonline.com/doi/full/10.1080/00401706.2024.2315937)
If you have used our code for research purposes, please cite the publication mentioned above. For the sake of simplicity, we provide the Bibtex format:
```bibtex
@Article{Zhao2024EPBO,
author = {Zhao, Jiangyan and Xu, Jin},
journal = {Technometrics},
title = {Bayesian Optimization via Exact Penalty},
year = {2024},
doi = {10.1080/00401706.2024.2315937},
}
@software{Zhao_EPBO_Bayesian_Optimization_2023,
author = {Zhao, Jiangyan and Xu, Jin},
month = dec,
title = {{EPBO: Bayesian Optimization via Exact Penalty}},
url = {https://github.com/Jiangyan-Zhao/EPBO},
version = {0.1.0},
year = {2023}
}
```