On the Convergence and Robustness of Adversarial Training

15 December 2021

Quanquan Gu

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

50 / 211 papers shown

Title
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP Hanxun Huang Sarah Monazam Erfani Yige Li Xingjun Ma James Bailey AAML 44 0 0 08 May 2025
MMARD: Improving the Min-Max Optimization Process in Adversarial Robustness Distillation Yuzheng Wang Zhaoyu Chen Dingkang Yang Yuanhang Wang Lizhe Qi AAML 69 0 0 09 Mar 2025
New Perspectives on Regularization and Computation in Optimal Transport-Based Distributionally Robust Optimization Soroosh Shafieezadeh-Abadeh Liviu Aolaritei Florian Dorfler Daniel Kuhn 60 20 0 31 Dec 2024
FAIR-TAT: Improving Model Fairness Using Targeted Adversarial Training Tejaswini Medi Steffen Jung M. Keuper AAML 44 3 0 30 Oct 2024
CausAdv: A Causal-based Framework for Detecting Adversarial Examples Hichem Debbi CML AAML 44 1 0 29 Oct 2024
Adversarial Training: A Survey Mengnan Zhao Lihe Zhang Jingwen Ye Huchuan Lu Baocai Yin Xinchao Wang AAML 28 1 0 19 Oct 2024
Stochastic Gradient Descent Jittering for Inverse Problems: Alleviating the Accuracy-Robustness Tradeoff Peimeng Guan Mark A. Davenport 33 0 0 18 Oct 2024
Adversarial Robustness Overestimation and Instability in TRADES Jonathan Weiping Li Ren-Wei Liang Cheng-Han Yeh Cheng-Chang Tsai Kuanchun Yu Chun-Shien Lu Shang-Tse Chen AAML 53 0 0 10 Oct 2024
Trustworthy Text-to-Image Diffusion Models: A Timely and Focused Survey Yi Zhang Zhen Chen Chih-Hong Cheng Wenjie Ruan Xiaowei Huang Dezong Zhao David Flynn Siddartha Khastgir Xingyu Zhao MedIm 44 3 0 26 Sep 2024
FedProphet: Memory-Efficient Federated Adversarial Training via Robust and Consistent Cascade Learning Minxue Tang Yitu Wang Jingyang Zhang Louis DiValentin Aolin Ding Amin Hass Yiran Chen Hai "Helen" Li FedML AAML 29 0 0 12 Sep 2024
TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors Yichuan Mo Hui Huang Mingjie Li Ang Li Yisen Wang AAML DiffM 32 16 0 09 Sep 2024
Attack Anything: Blind DNNs via Universal Background Adversarial Attack Jiawei Lian Shaohui Mei Xiaofei Wang Yi Wang Lefan Wang Yingjie Lu Mingyang Ma Lap-Pui Chau AAML 39 1 0 17 Aug 2024
AdvQDet: Detecting Query-Based Adversarial Attacks with Adversarial Contrastive Prompt Tuning Xin Wang Kai-xiang Chen Xingjun Ma Zhineng Chen Jingjing Chen Yu-Gang Jiang AAML 43 3 0 04 Aug 2024
MeanSparse: Post-Training Robustness Enhancement Through Mean-Centered Feature Sparsification Sajjad Amini Mohammadreza Teymoorianfard Shiqing Ma Amir Houmansadr OOD AAML 37 6 0 09 Jun 2024
Perturbation Towards Easy Samples Improves Targeted Adversarial Transferability Junqi Gao Biqing Qi Yao Li Zhichang Guo Dong Li Yuming Xing Dazhi Zhang AAML 34 6 0 08 Jun 2024
Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training Jiacheng Zhang Feng Liu Dawei Zhou Jingfeng Zhang Tongliang Liu AAML 43 2 0 02 Jun 2024
PUMA: margin-based data pruning Javier Maroto Pascal Frossard AAML 42 1 0 10 May 2024
SSCAE -- Semantic, Syntactic, and Context-aware natural language Adversarial Examples generator J. Asl Mohammad H. Rafiei Manar Alohaly Daniel Takabi AAML SILM 31 3 0 18 Mar 2024
Analysis of Kernel Mirror Prox for Measure Optimization Pavel Dvurechensky Jia Jie Zhu 31 2 0 29 Feb 2024
Investigating Deep Watermark Security: An Adversarial Transferability Perspective Biqing Qi Junqi Gao Yiang Luo Jianxing Liu Ligang Wu Bowen Zhou AAML 31 3 0 26 Feb 2024
Distilling Adversarial Robustness Using Heterogeneous Teachers Jieren Deng A. Palmer Rigel Mahmood Ethan Rathbun Jinbo Bi Kaleel Mahmood Derek Aguiar AAML 43 0 0 23 Feb 2024
ProTIP: Probabilistic Robustness Verification on Text-to-Image Diffusion Models against Stochastic Perturbation Yi Zhang Yun Tang Wenjie Ruan Xiaowei Huang Siddartha Khastgir P. Jennings Xingyu Zhao AAML 29 4 0 23 Feb 2024
Fight Back Against Jailbreaking via Prompt Adversarial Tuning Yichuan Mo Yuji Wang Zeming Wei Yisen Wang AAML SILM 49 25 0 09 Feb 2024
Seeing is not always believing: The Space of Harmless Perturbations Lu Chen Shaofeng Li Benhao Huang Fan Yang Zheng Li Jie Li Yuan Luo AAML 8 0 0 03 Feb 2024
Unlearnable Examples For Time Series Yujing Jiang Xingjun Ma S. Erfani James Bailey AI4TS 23 1 0 03 Feb 2024
Better Representations via Adversarial Training in Pre-Training: A Theoretical Perspective Yue Xing Xiaofeng Lin Qifan Song Yi Tian Xu Belinda Zeng Guang Cheng SSL 26 0 0 26 Jan 2024
Towards Robust Semantic Segmentation against Patch-based Attack via Attention Refinement Zheng Yuan Jie Zhang Yude Wang Shiguang Shan Xilin Chen AAML 40 1 0 03 Jan 2024
The Adaptive Arms Race: Redefining Robustness in AI Security Ilias Tsingenopoulos Vera Rimmer Davy Preuveneers Fabio Pierazzi Lorenzo Cavallaro Wouter Joosen AAML 72 0 0 20 Dec 2023
Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off Yuansan Liu Ruqing Zhang Mingkun Zhang Wei Chen Maarten de Rijke J. Guo Xueqi Cheng AAML 22 6 0 16 Dec 2023
Defenses in Adversarial Machine Learning: A Survey Baoyuan Wu Shaokui Wei Mingli Zhu Meixi Zheng Zihao Zhu Mingda Zhang Hongrui Chen Danni Yuan Li Liu Qingshan Liu AAML 30 14 0 13 Dec 2023
Outlier-Robust Wasserstein DRO Sloan Nietert Ziv Goldfeld Soroosh Shafiee 34 9 0 09 Nov 2023
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
Adversarial Examples Are Not Real Features Ang Li Yifei Wang Yiwen Guo Yisen Wang 20 11 0 29 Oct 2023
Fast Propagation is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetworks Xiaojun Jia Jianshu Li Jindong Gu Yang Bai Xiaochun Cao AAML 24 9 0 24 Oct 2023
Splitting the Difference on Adversarial Training Matan Levi A. Kontorovich 40 4 0 03 Oct 2023
Reducing Adversarial Training Cost with Gradient Approximation Huihui Gong AAML 19 0 0 18 Sep 2023
Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff Satoshi Suzuki Shinýa Yamaguchi Shoichiro Takeda Sekitoshi Kanai Naoki Makishima Atsushi Ando Ryo Masumura AAML 30 4 0 31 Aug 2023
Robust Principles: Architectural Design Principles for Adversarially Robust CNNs Sheng-Hsuan Peng Weilin Xu Cory Cornelius Matthew Hull Kevin Li Rahul Duggal Mansi Phute Jason Martin Duen Horng Chau AAML 21 46 0 30 Aug 2023
Advancing Adversarial Robustness Through Adversarial Logit Update Hao Xuan Peican Zhu Xingyu Li AAML 26 0 0 29 Aug 2023
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging Xiaojun Jia YueFeng Chen Xiaofeng Mao Ranjie Duan Jindong Gu Rong Zhang H. Xue Xiaochun Cao AAML 19 9 0 22 Aug 2023
Sup-Norm Convergence of Deep Neural Network Estimator for Nonparametric Regression by Adversarial Training Masaaki Imaizumi AAML 13 4 0 08 Jul 2023
Robust Ranking Explanations Chao Chen Chenghua Guo Guixiang Ma Ming Zeng Xi Zhang Sihong Xie FAtt AAML 35 0 0 08 Jul 2023
Transgressing the boundaries: towards a rigorous understanding of deep learning and its (non-)robustness C. Hartmann Lorenz Richter AAML 27 2 0 05 Jul 2023
Brightness-Restricted Adversarial Attack Patch Mingzhen Shao AAML 6 1 0 01 Jul 2023
DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization Songyang Gao Shihan Dou Yan Liu Xiao Wang Qi Zhang Zhongyu Wei Jin Ma Yingchun Shan OOD 19 3 0 27 Jun 2023
Adversarial Training with Generated Data in High-Dimensional Regression: An Asymptotic Study Yue Xing 22 0 0 21 Jun 2023
On Achieving Optimal Adversarial Test Error Justin D. Li Matus Telgarsky AAML 25 1 0 13 Jun 2023
Enhance Diffusion to Improve Robust Generalization Jianhui Sun Sanchit Sinha Aidong Zhang 32 4 0 05 Jun 2023
ChatGPT-Like Large-Scale Foundation Models for Prognostics and Health Management: A Survey and Roadmaps Yanfang Li Huan Wang Muxia Sun LM&MA AI4TS AI4CE 29 46 0 10 May 2023
Sharpness-Aware Minimization Alone can Improve Adversarial Robustness Zeming Wei Jingyu Zhu Yihao Zhang AAML 30 10 0 09 May 2023