Fanny Yang, Zuowen Wang, Christina Heinze-Deml. Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness. In Hanna M. Wallach, Hugo Larochelle, Alina Beygelzimer, Florence d'Alché-Buc, Edward A. Fox, Roman Garnett, editors, Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14 December 2019, Vancouver, BC, Canada. pages 14757-14768, 2019. [doi]
@inproceedings{YangWH19,
title = {Invariance-inducing regularization using worst-case transformations suffices to boost accuracy and spatial robustness},
author = {Fanny Yang and Zuowen Wang and Christina Heinze-Deml},
year = {2019},
url = {http://papers.nips.cc/paper/9618-invariance-inducing-regularization-using-worst-case-transformations-suffices-to-boost-accuracy-and-spatial-robustness},
researchr = {https://researchr.org/publication/YangWH19},
cites = {0},
citedby = {0},
pages = {14757-14768},
booktitle = {Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, 8-14 December 2019, Vancouver, BC, Canada},
editor = {Hanna M. Wallach and Hugo Larochelle and Alina Beygelzimer and Florence d'Alché-Buc and Edward A. Fox and Roman Garnett},
}