On Batch Bayesian Optimization
Machine Learning
2019-11-05 v1 Machine Learning
Abstract
We present two algorithms for Bayesian optimization in the batch feedback setting, based on Gaussian process upper confidence bound and Thompson sampling approaches, along with frequentist regret guarantees and numerical results.
Keywords
Cite
@article{arxiv.1911.01032,
title = {On Batch Bayesian Optimization},
author = {Sayak Ray Chowdhury and Aditya Gopalan},
journal= {arXiv preprint arXiv:1911.01032},
year = {2019}
}
Comments
All of Bayesian Nonparametrics workshop, Neural Information Processing Systems, 2018