From: ICML.cc/2021/Workshop/AML/Program_Chairs
title: Paper Decision
decision: Accept (Poster)
comment: This paper proposed an adaptive Frank-Wolfe adversarial training method to improve robustness, achieving comparable robustness with PGD-AT while significantly decreasing training time.

From: ICML.cc/2021/Workshop/AML/Paper24/Reviewer_bQqH
title: A promising alternative to PGD-AT
review: The paper uses the Frank-Wolfe optimization to derive a relationship between loss landscape and attack distortion. Based on this relationship the authors propose an adaptive Frank-Wolfe adversarial training (FW-AT-Adapt) method to obtain robustness. This method can achieve robustness near or above multistep PGD-AT while significantly decreasing training time. Briefly, the paper provides a promising alternative to PGD-AT.

This work may shed light on future research on the connecting Frank-Wolfe optimization and adversarial robustness.
rating: Accept
confidence: 3: The reviewer is fairly confident that the evaluation is correct