Identifying Adversarially Attackable and Robust Samples

30 January 2023

Papers citing "Identifying Adversarially Attackable and Robust Samples"

4 / 4 papers shown

Title
A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies Zhuang Qian Kaizhu Huang Qiufeng Wang Xu-Yao Zhang OOD AAML ObjD 47 71 0 26 Mar 2022
Adversarial Attacks on Speech Recognition Systems for Mission-Critical Applications: A Survey Ngoc Dung Huynh Mohamed Reda Bouadjenek Imran Razzak Kevin Lee Chetan Arora Ali Hassani A. Zaslavsky AAML 21 6 0 22 Feb 2022
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao B. Wen Qian Wang AAML 71 467 0 02 Feb 2021
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 256 3,102 0 04 Nov 2016