aryandeshwal/mesmo

Python implementation of the Max-value Entropy Search for Multi-Objective Bayesian Optimization method

Max-value Entropy Search for Multi-Objective Bayesian Optimization

This repository contains the python implementation for MESMO from the Neurips 2019 paper "Max-value Entropy Search for Multi-ObjectiveBayesian Optimization".

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 please cite our papers:

@inproceedings{belakaria2019max,
  title={Max-value entropy search for multi-objective bayesian optimization},
  author={Belakaria, Syrine and Deshwal, Aryan},
  booktitle={International Conference on Neural Information Processing Systems (NeurIPS)},
  year={2019}
}

@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}
}