This repository is to re-implement several baseline methods in batch Bayesian optimization, using BayesO.
- Batch Bayesian optimization with random query selection
- Batch Bayesian optimization with a kriging believer
David Ginsbourger, Rodolphe Le Riche, and Laurent Carraro.
"Kriging is well-suited to parallelize optimization."
Computational intelligence in expensive optimization problems,
pp. 131-162. 2010.
David Ginsbourger, Rodolphe Le Riche, and Laurent Carraro.
"Kriging is well-suited to parallelize optimization."
Computational intelligence in expensive optimization problems,
pp. 131-162. 2010.
Emile Contal, David Buffoni, Alexandre Robicquet, and Nicolas Vayatis.
"Parallel Gaussian process optimization with upper confidence bound and pure exploration."
In Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases,
pp. 225-240. 2013.
Javier Gonzalez, Zhenwen Dai, Philipp Hennig, Neil Lawrence.
"Batch Bayesian optimization via local penalization."
In Proceedings of the International Conference on Artificial Intelligence and Statistics,
pp. 648-657. 2016.
We recommend installing it with virtualenv.
You can choose one of the following installation options.
- Using source code (for developer installation)
To install batch-bayeso from source code, command it in the batch-bayeso root.
pip install .- Using source code (for editable development mode)
To use editable development mode, command it in the batch-bayeso root.
pip install -e .In addition, you can add [examples] in order to install the packages required for the examples included in the batch-bayeso repository.
For example, pip install .[examples] or pip install -e .[examples].
- Uninstallation
If you would like to uninstall batch-bayeso, command it.
$ pip uninstall batch-bayeso