Learn from the Past: A Proxy Guided Adversarial Defense Framework with Self Distillation Regularization

19 October 2023

Papers citing "Learn from the Past: A Proxy Guided Adversarial Defense Framework with Self Distillation Regularization"

5 / 5 papers shown

Title
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong Liyuan Liu Jingbo Shang NoLa AAML 56 18 0 07 Oct 2021
Meta Gradient Adversarial Attack Zheng Yuan Jie Zhang Yunpei Jia Chuanqi Tan Tao Xue Shiguang Shan AAML 49 78 0 09 Aug 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 231 677 0 19 Oct 2020
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 202 243 0 14 Jun 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,837 0 08 Jul 2016