On the Convergence and Robustness of Adversarial Training

On the Convergence and Robustness of Adversarial Training

15 December 2021

Quanquan Gu

Papers citing "On the Convergence and Robustness of Adversarial Training"

11 / 211 papers shown

Title
Where is the Bottleneck of Adversarial Learning with Unlabeled Data? Jingfeng Zhang Bo Han Gang Niu Tongliang Liu Masashi Sugiyama 30 6 0 20 Nov 2019
Smoothed Inference for Adversarially-Trained Models Yaniv Nemcovsky Evgenii Zheltonozhskii Chaim Baskin Brian Chmiel Maxim Fishman A. Bronstein A. Mendelson AAML FedML 24 2 0 17 Nov 2019
Coverage Guided Testing for Recurrent Neural Networks Wei Huang Youcheng Sun Xing-E. Zhao James Sharp Wenjie Ruan Jie Meng Xiaowei Huang AAML 25 47 0 05 Nov 2019
Confidence-Calibrated Adversarial Training: Generalizing to Unseen Attacks David Stutz Matthias Hein Bernt Schiele AAML 22 5 0 14 Oct 2019
Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems Xingjun Ma Yuhao Niu Lin Gu Yisen Wang Yitian Zhao James Bailey Feng Lu MedIm AAML 27 445 0 24 Jul 2019
Convergence of Adversarial Training in Overparametrized Neural Networks Ruiqi Gao Tianle Cai Haochuan Li Liwei Wang Cho-Jui Hsieh J. Lee AAML 13 107 0 19 Jun 2019
Adversarially Robust Generalization Just Requires More Unlabeled Data Runtian Zhai Tianle Cai Di He Chen Dan Kun He J. Hopcroft Liwei Wang 9 154 0 03 Jun 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data Amir Najafi S. Maeda Masanori Koyama Takeru Miyato OOD 18 129 0 24 May 2019
Black-box Adversarial Attacks on Video Recognition Models Linxi Jiang Xingjun Ma Shaoxiang Chen James Bailey Yu-Gang Jiang AAML MLAU 9 142 0 10 Apr 2019
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 21 270 0 06 Dec 2018
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 293 5,842 0 08 Jul 2016