Class or Function Names PIMSSampler Installation $ pip install -r https://hub.optuna.org/samplers/gp_pims/requirements.txt Example Please see example.py.
Others Reference Shion Takeno, Yu Inatsu, Masayuki Karasuyama, Ichiro Takeuchi, Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds, Proceedings of the 41st International Conference on Machine Learning, PMLR 235:47510-47534, 2024.
Bibtex @InProceedings{pmlr-v235-takeno24a, title = {Posterior Sampling-Based {B}ayesian Optimization with Tighter {B}ayesian Regret Bounds}, author = {Takeno, Shion and Inatsu, Yu and Karasuyama, Masayuki and Takeuchi, Ichiro}, booktitle = {Proceedings of the 41st International Conference on Machine Learning}, pages = {47510--47534}, year = {2024}, editor = {Salakhutdinov, Ruslan and Kolter, Zico and Heller, Katherine and Weller, Adrian and Oliver, Nuria and Scarlett, Jonathan and Berkenkamp, Felix}, volume = {235}, series = {Proceedings of Machine Learning Research}, month = {21--27 Jul}, publisher = {PMLR}, pdf = {https://raw.
Class or Function Names MeanVarianceAnalysisScalarizationSimulatorSampler Installation $ pip install scipy Example Please see example.ipynb
Others For example, you can add sections to introduce a corresponding paper.
Reference Iwazaki, Shogo, Yu Inatsu, and Ichiro Takeuchi. “Mean-variance analysis in Bayesian optimization under uncertainty.” International Conference on Artificial Intelligence and Statistics. PMLR, 2021.
Bibtex @inproceedings{iwazaki2021mean, title={Mean-variance analysis in Bayesian optimization under uncertainty}, author={Iwazaki, Shogo and Inatsu, Yu and Takeuchi, Ichiro}, booktitle={International Conference on Artificial Intelligence and Statistics}, pages={973--981}, year={2021}, organization={PMLR} }
APIs A sampler that uses SMAC3 v2.2.0 verified by unittests that can be run by the following:
$ pip install pytest optunahub smac $ python -m pytest package/samplers/smac_sampler/tests/ Please check the API reference for more details:
https://automl.github.io/SMAC3/main/5_api.html SMACSampler(search_space: dict[str, BaseDistribution], n_trials: int = 100, seed: int | None = None, *, surrogate_model_type: str = "rf", acq_func_type: str = "ei_log", init_design_type: str = "sobol", surrogate_model_rf_num_trees: int = 10, surrogate_model_rf_ratio_features: float = 1.