NeurIPS 2019
Sun Dec 8th through Sat the 14th, 2019 at Vancouver Convention Center
Paper ID:6030
Title:Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers

This work shows how to improve the previous state of the art for L2 robustness using smoothed classifiers (introduced by Cohen et al.) The empirical results are very strong in a very competitive area where many research groups are competing. The theoretical work, the presentation and the various technical details involved in using smoothness in PGD are all great contributions. This is an important paper in the space of adversarial ML.