Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization

Samuel Daulton, Maximilian Balandat, Eytan Bakshy. Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization. In Hugo Larochelle, Marc'Aurelio Ranzato, Raia Hadsell, Maria-Florina Balcan, Hsuan-Tien Lin, editors, Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual. 2020. [doi]

@inproceedings{DaultonBB20,
  title = {Differentiable Expected Hypervolume Improvement for Parallel Multi-Objective Bayesian Optimization},
  author = {Samuel Daulton and Maximilian Balandat and Eytan Bakshy},
  year = {2020},
  url = {https://proceedings.neurips.cc/paper/2020/hash/6fec24eac8f18ed793f5eaad3dd7977c-Abstract.html},
  researchr = {https://researchr.org/publication/DaultonBB20},
  cites = {0},
  citedby = {0},
  booktitle = {Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual},
  editor = {Hugo Larochelle and Marc'Aurelio Ranzato and Raia Hadsell and Maria-Florina Balcan and Hsuan-Tien Lin},
}