Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints

This repository contains the python implementation for MESMOC the paper "Max-value Entropy Search for Multi-Objective Bayesian Optimization with Constraints".

Requirements

The code is implemented in Python and requires the following packages:

1. sobol_seq

2. platypus

3. sklearn.gaussian_process

4. pygmo

Citation

If you use this code in your academic work please cite our papers:

@article{belakaria2021output,
  title={Output Space Entropy Search Framework for Multi-Objective Bayesian Optimization},
  author={Belakaria, Syrine and Deshwal, Aryan and Doppa, Janardhan Rao},
  journal={Journal of Artificial Intelligence Research},
  volume={72},
  pages={667-715},
  year={2021}
}

@article{belakaria2020max,
  title={Max-value entropy search for multi-objective Bayesian optimization with constraints},
  author={Belakaria, Syrine and Deshwal, Aryan and Doppa, Janardhan Rao},
  journal={Workshop on Machine Learning and the Physical Sciences (NeurIPS)},
  year={2020}
}