NeurIPS 2019poster55 citations
Offline Contextual Bayesian Optimization
Ian Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Andrew Oakleigh Nelson, Mark Boyer, Egemen Kolemen, Jeff Schneider
Abstract
In black-box optimization, an agent repeatedly chooses a configuration to test, so as to find an optimal configuration. In many practical problems of interest, one would like to optimize several systems, or
BibTeX
@inproceedings{NEURIPS2019_7876acb6,
author = {Char, Ian and Chung, Youngseog and Neiswanger, Willie and Kandasamy, Kirthevasan and Nelson, Andrew Oakleigh and Boyer, Mark and Kolemen, Egemen and Schneider, Jeff},
booktitle = {Advances in Neural Information Processing Systems},
editor = {H. Wallach and H. Larochelle and A. Beygelzimer and F. d\textquotesingle Alch\'{e}-Buc and E. Fox and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Offline Contextual Bayesian Optimization},
url = {https://proceedings.neurips.cc/paper_files/paper/2019/file/7876acb66640bad41f1e1371ef30c180-Paper.pdf},
volume = {32},
year = {2019}
}