Learnable Boundary Guided Adversarial Training

23 November 2020

Papers citing "Learnable Boundary Guided Adversarial Training"

50 / 86 papers shown

Title
Revisiting the Relationship between Adversarial and Clean Training: Why Clean Training Can Make Adversarial Training Better MingWei Zhou Xiaobing Pei AAML 106 0 0 30 Mar 2025
Enhancing Robust Fairness via Confusional Spectral Regularization Gaojie Jin Sihao Wu Jiaxu Liu Tianjin Huang Ronghui Mu 74 1 0 22 Jan 2025
Adversarial Training: A Survey Mengnan Zhao Lihe Zhang Jingwen Ye Huchuan Lu Baocai Yin Xinchao Wang AAML 28 0 0 19 Oct 2024
Hyper Adversarial Tuning for Boosting Adversarial Robustness of Pretrained Large Vision Models Kangtao Lv Huangsen Cao Kainan Tu Yihuai Xu Zhimeng Zhang Xin Ding Yongwei Wang MoMe AAML VLM 19 1 0 08 Oct 2024
Improving Fast Adversarial Training via Self-Knowledge Guidance Chengze Jiang Junkai Wang Minjing Dong Jie Gui Xinli Shi Yuan Cao Yuan Yan Tang James Tin-Yau Kwok 29 1 0 26 Sep 2024
Dynamic Label Adversarial Training for Deep Learning Robustness Against Adversarial Attacks Zhenyu Liu Haoran Duan Huizhi Liang Yang Long V. Snás̃el G. Nicosia R. Ranjan Varun Ojha AAML 29 0 0 23 Aug 2024
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness Kejia Zhang Juanjuan Weng Yuanzheng Cai Zhiming Luo Shaozi Li AAML 57 0 0 04 Jul 2024
Harmonizing Feature Maps: A Graph Convolutional Approach for Enhancing Adversarial Robustness Kejia Zhang Juanjuan Weng Junwei Wu Guoqing Yang Shaozi Li Zhiming Luo AAML 38 0 0 17 Jun 2024
The Pitfalls and Promise of Conformal Inference Under Adversarial Attacks Ziquan Liu Yufei Cui Yan Yan Yi Tian Xu Xiangyang Ji Xue Liu Antoni B. Chan AAML 25 2 0 14 May 2024
On adversarial training and the 1 Nearest Neighbor classifier Amir Hagai Yair Weiss AAML 50 0 0 09 Apr 2024
STBA: Towards Evaluating the Robustness of DNNs for Query-Limited Black-box Scenario Renyang Liu Kwok-Yan Lam Wei Zhou Sixing Wu Jun Zhao Dongting Hu Mingming Gong AAML 24 0 0 30 Mar 2024
Dynamic Perturbation-Adaptive Adversarial Training on Medical Image Classification Shuai Li Xiaoguang Ma Shancheng Jiang Lu Meng AAML OOD 30 0 0 11 Mar 2024
SoK: Analyzing Adversarial Examples: A Framework to Study Adversary Knowledge L. Fenaux Florian Kerschbaum AAML 29 0 0 22 Feb 2024
Rethinking Invariance Regularization in Adversarial Training to Improve Robustness-Accuracy Trade-off Futa Waseda Ching-Chun Chang Isao Echizen AAML 29 0 0 22 Feb 2024
Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off Yuansan Liu Ruqing Zhang Mingkun Zhang Wei-Neng Chen Maarten de Rijke J. Guo Xueqi Cheng AAML 14 6 0 16 Dec 2023
Topology-Preserving Adversarial Training Xiaoyue Mi Fan Tang Yepeng Weng Danding Wang Juan Cao Sheng Tang Peng Li Yang Liu 47 1 0 29 Nov 2023
Fast Propagation is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetworks Xiaojun Jia Jianshu Li Jindong Gu Yang Bai Xiaochun Cao AAML 22 9 0 24 Oct 2023
Semantic-Aware Adversarial Training for Reliable Deep Hashing Retrieval Xu Yuan Zheng-Wei Zhang Xunguang Wang Lin Wu AAML 26 11 0 23 Oct 2023
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks Yue Cao Tianlin Li Xiaofeng Cao Ivor Tsang Yang Liu Qing-Wu Guo AAML 21 2 0 18 Oct 2023
Splitting the Difference on Adversarial Training Matan Levi A. Kontorovich 32 4 0 03 Oct 2023
Exploring Robust Features for Improving Adversarial Robustness Hong Wang Yuefan Deng Shinjae Yoo Yuewei Lin AAML 21 4 0 09 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 28 4 0 31 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 11 9 0 22 Aug 2023
Improving Adversarial Robustness of Masked Autoencoders via Test-time Frequency-domain Prompting Qidong Huang Xiaoyi Dong Dongdong Chen Yinpeng Chen Lu Yuan Gang Hua Weiming Zhang Neng H. Yu AAML 11 8 0 20 Aug 2023
Towards Building More Robust Models with Frequency Bias Qingwen Bu Dong Huang Heming Cui AAML 15 10 0 19 Jul 2023
Post-train Black-box Defense via Bayesian Boundary Correction He-Nan Wang Yunfeng Diao AAML 31 1 0 29 Jun 2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World Weiran Lin Keane Lucas Neo Eyal Lujo Bauer Michael K. Reiter Mahmood Sharif OOD AAML 22 1 0 29 Jun 2023
Revisiting and Advancing Adversarial Training Through A Simple Baseline Hong Liu AAML 24 0 0 13 Jun 2023
Decoupled Kullback-Leibler Divergence Loss Jiequan Cui Zhuotao Tian Zhisheng Zhong Xiaojuan Qi Bei Yu Hanwang Zhang 34 38 0 23 May 2023
Annealing Self-Distillation Rectification Improves Adversarial Training Yuehua Wu Hung-Jui Wang Shang-Tse Chen AAML 24 3 0 20 May 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 30 48 0 18 May 2023
Certified Zeroth-order Black-Box Defense with Robust UNet Denoiser Astha Verma A. Subramanyam Siddhesh Bangar Naman Lal R. Shah Shiníchi Satoh 27 4 0 13 Apr 2023
To be Robust and to be Fair: Aligning Fairness with Robustness Junyi Chai Xiaoqian Wang 28 2 0 31 Mar 2023
Beyond Empirical Risk Minimization: Local Structure Preserving Regularization for Improving Adversarial Robustness Wei Wei Jiahuan Zhou Yingying Wu AAML 13 0 0 29 Mar 2023
CAT:Collaborative Adversarial Training Xingbin Liu Huafeng Kuang Xianming Lin Yongjian Wu Rongrong Ji AAML 17 4 0 27 Mar 2023
PIAT: Parameter Interpolation based Adversarial Training for Image Classification Kun He Xin Liu Yichen Yang Zhou Qin Weigao Wen Hui Xue J. Hopcroft AAML 14 0 0 24 Mar 2023
Feature Separation and Recalibration for Adversarial Robustness Woo Jae Kim Y. Cho Junsik Jung Sung-eui Yoon AAML 36 18 0 24 Mar 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 31 34 0 19 Mar 2023
Delving into the Adversarial Robustness of Federated Learning Jie M. Zhang Bo-wen Li Chen Chen Lingjuan Lyu Shuang Wu Shouhong Ding Chao Wu FedML 30 34 0 19 Feb 2023
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness Yuancheng Xu Yanchao Sun Micah Goldblum Tom Goldstein Furong Huang AAML 18 37 0 06 Feb 2023
Beckman Defense A. V. Subramanyam OOD AAML 27 0 0 04 Jan 2023
DISCO: Adversarial Defense with Local Implicit Functions Chih-Hui Ho Nuno Vasconcelos AAML 21 38 0 11 Dec 2022
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles Shengcai Liu Fu Peng Ke Tang AAML 31 11 0 23 Nov 2022
The Enemy of My Enemy is My Friend: Exploring Inverse Adversaries for Improving Adversarial Training Junhao Dong Seyed-Mohsen Moosavi-Dezfooli Jianhuang Lai Xiaohua Xie AAML 35 28 0 01 Nov 2022
On the Robustness of Dataset Inference S. Szyller Rui Zhang Jian Liu Nadarajah Asokan AAML 15 6 0 24 Oct 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 19 24 0 12 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 25 5 0 11 Oct 2022
Pruning Adversarially Robust Neural Networks without Adversarial Examples T. Jian Zifeng Wang Yanzhi Wang Jennifer Dy Stratis Ioannidis AAML VLM 39 11 0 09 Oct 2022
Robust Ensemble Morph Detection with Domain Generalization Hossein Kashiani S. Sami Sobhan Soleymani Nasser M. Nasrabadi OOD AAML 11 8 0 16 Sep 2022
PointCAT: Contrastive Adversarial Training for Robust Point Cloud Recognition Qidong Huang Xiaoyi Dong Dongdong Chen Hang Zhou Weiming Zhang Kui Zhang Gang Hua Nenghai Yu 3DPC 19 12 0 16 Sep 2022