Class or Function Names
- HEBOSampler
Installation
pip install -r requirements.txt
git clone git@github.com:huawei-noah/HEBO.git
cd HEBO/HEBO
pip install -e .
Example
search_space = {
"x": FloatDistribution(-10, 10),
"y": IntDistribution(0, 10),
}
sampler = HEBOSampler(search_space)
study = optuna.create_study(sampler=sampler)
See example.py
for a full example.
Others
HEBO is the winning submission to the NeurIPS 2020 Black-Box Optimisation Challenge. Please refer to the official repository of HEBO for more details.
Reference
Cowen-Rivers, Alexander I., et al. “An Empirical Study of Assumptions in Bayesian Optimisation.” arXiv preprint arXiv:2012.03826 (2021).