Han Bao, Clayton Scott, Masashi Sugiyama. Calibrated Surrogate Losses for Adversarially Robust Classification. In Jacob D. Abernethy, Shivani Agarwal 0001, editors, Conference on Learning Theory, COLT 2020, 9-12 July 2020, Virtual Event [Graz, Austria]. Volume 125 of Proceedings of Machine Learning Research, pages 408-451, PMLR, 2020. [doi]
@inproceedings{BaoSS20,
title = {Calibrated Surrogate Losses for Adversarially Robust Classification},
author = {Han Bao and Clayton Scott and Masashi Sugiyama},
year = {2020},
url = {http://proceedings.mlr.press/v125/bao20a.html},
researchr = {https://researchr.org/publication/BaoSS20},
cites = {0},
citedby = {0},
pages = {408-451},
booktitle = {Conference on Learning Theory, COLT 2020, 9-12 July 2020, Virtual Event [Graz, Austria]},
editor = {Jacob D. Abernethy and Shivani Agarwal 0001},
volume = {125},
series = {Proceedings of Machine Learning Research},
publisher = {PMLR},
}