Fooling Adversarial Training with Inducing Noise

19 November 2021

Papers citing "Fooling Adversarial Training with Inducing Noise"

6 / 6 papers shown

Title
Nonlinear Transformations Against Unlearnable Datasets T. Hapuarachchi Jing Lin Kaiqi Xiong Mohamed Rahouti Gitte Ost 28 1 0 05 Jun 2024
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective Yifei Wang Liangchen Li Jiansheng Yang Zhouchen Lin Yisen Wang 31 11 0 30 Oct 2023
Unlearnable Examples Give a False Sense of Security: Piercing through Unexploitable Data with Learnable Examples Wanzhu Jiang Yunfeng Diao He Wang Jianxin Sun Hao Wu Richang Hong 37 18 0 16 May 2023
Can Adversarial Training Be Manipulated By Non-Robust Features? Lue Tao Lei Feng Hongxin Wei Jinfeng Yi Sheng-Jun Huang Songcan Chen AAML 95 16 0 31 Jan 2022
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 156 190 0 13 Jan 2021
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 293 3,110 0 04 Nov 2016