Disentangling Adversarial Robustness and Generalization

3 December 2018

David Stutz

Matthias Hein

Bernt Schiele

AAML

OOD

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Papers citing "Disentangling Adversarial Robustness and Generalization"

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Title
Passive Deepfake Detection Across Multi-modalities: A Comprehensive Survey Hong-Hanh Nguyen-Le Van-Tuan Tran Dinh-Thuc Nguyen Nhien-An Le-Khac AAML 110 1 0 26 Nov 2024
ADBM: Adversarial diffusion bridge model for reliable adversarial purification Xiao-Li Li Wenxuan Sun Huanran Chen Qiongxiu Li Yining Liu Yingzhe He Jie Shi Xiaolin Hu AAML 58 7 0 01 Aug 2024
Exploiting the Layered Intrinsic Dimensionality of Deep Models for Practical Adversarial Training Enes Altinisik Safa Messaoud H. Sencar Hassan Sajjad Sanjay Chawla AAML 48 0 0 27 May 2024
Rényi Neural Processes Xuesong Wang He Zhao Edwin V. Bonilla UQCV BDL 32 0 0 25 May 2024
Training Image Derivatives: Increased Accuracy and Universal Robustness V. Avrutskiy 46 0 0 21 Oct 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao René Vidal 26 8 0 28 Sep 2023
Input margins can predict generalization too Coenraad Mouton Marthinus W. Theunissen Marelie Hattingh Davel AAML UQCV AI4CE 23 3 0 29 Aug 2023
Why Does Little Robustness Help? Understanding and Improving Adversarial Transferability from Surrogate Training Yechao Zhang Shengshan Hu Leo Yu Zhang Junyu Shi Minghui Li Xiaogeng Liu Wei Wan Hai Jin AAML 22 21 0 15 Jul 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 24 208 0 09 Feb 2023
Towards Adversarial Realism and Robust Learning for IoT Intrusion Detection and Classification João Vitorino Isabel Praça Eva Maia AAML 29 28 0 30 Jan 2023
Understanding Zero-Shot Adversarial Robustness for Large-Scale Models Chengzhi Mao Scott Geng Junfeng Yang Xin Eric Wang Carl Vondrick VLM 42 59 0 14 Dec 2022
Leveraging Unlabeled Data to Track Memorization Mahsa Forouzesh Hanie Sedghi Patrick Thiran NoLa TDI 34 3 0 08 Dec 2022
Learning Antidote Data to Individual Unfairness Peizhao Li Ethan Xia Hongfu Liu FedML FaML 19 9 0 29 Nov 2022
Understanding the Vulnerability of Skeleton-based Human Activity Recognition via Black-box Attack Yunfeng Diao He-Nan Wang Tianjia Shao Yong-Liang Yang Kun Zhou David C. Hogg Meng Wang AAML 37 6 0 21 Nov 2022
Textual Manifold-based Defense Against Natural Language Adversarial Examples D. M. Nguyen Anh Tuan Luu AAML 19 17 0 05 Nov 2022
An Adversarial Robustness Perspective on the Topology of Neural Networks Morgane Goibert Thomas Ricatte Elvis Dohmatob AAML 11 2 0 04 Nov 2022
Adversarial Purification with the Manifold Hypothesis Zhaoyuan Yang Zhiwei Xu Jing Zhang Richard I. Hartley Peter Tu AAML 21 5 0 26 Oct 2022
Strength-Adaptive Adversarial Training Chaojian Yu Dawei Zhou Li Shen Jun Yu Bo Han Biwei Huang Nannan Wang Tongliang Liu OOD 17 2 0 04 Oct 2022
Distance Learner: Incorporating Manifold Prior to Model Training Aditya Chetan Nipun Kwatra 21 1 0 14 Jul 2022
Aug-NeRF: Training Stronger Neural Radiance Fields with Triple-Level Physically-Grounded Augmentations Tianlong Chen Peihao Wang Zhiwen Fan Zhangyang Wang 36 55 0 04 Jul 2022
Domain Generalization via Selective Consistency Regularization for Time Series Classification Wenyu Zhang Mohamed Ragab Chuan-Sheng Foo OOD AI4TS 21 2 0 16 Jun 2022
On Fragile Features and Batch Normalization in Adversarial Training Nils Philipp Walter David Stutz Bernt Schiele AAML 19 5 0 26 Apr 2022
A Manifold View of Adversarial Risk Wen-jun Zhang Yikai Zhang Xiaoling Hu Mayank Goswami Chao Chen Dimitris N. Metaxas AAML 19 6 0 24 Mar 2022
Defending Black-box Skeleton-based Human Activity Classifiers He-Nan Wang Yunfeng Diao Zichang Tan G. Guo AAML 48 10 0 09 Mar 2022
Why adversarial training can hurt robust accuracy Jacob Clarysse Julia Hörrmann Fanny Yang AAML 13 18 0 03 Mar 2022
Robustness and Accuracy Could Be Reconcilable by (Proper) Definition Tianyu Pang Min-Bin Lin Xiao Yang Junyi Zhu Shuicheng Yan 30 119 0 21 Feb 2022
Layer-wise Regularized Adversarial Training using Layers Sustainability Analysis (LSA) framework Mohammad Khalooei M. Homayounpour M. Amirmazlaghani AAML 17 3 0 05 Feb 2022
How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness? Xinhsuai Dong Anh Tuan Luu Min-Bin Lin Shuicheng Yan Hanwang Zhang SILM AAML 20 55 0 22 Dec 2021
Interpolated Joint Space Adversarial Training for Robust and Generalizable Defenses Chun Pong Lau Jiang-Long Liu Hossein Souri Wei-An Lin S. Feizi Ramalingam Chellappa AAML 29 12 0 12 Dec 2021
Robust and Accurate Object Detection via Self-Knowledge Distillation Weipeng Xu Pengzhi Chu Renhao Xie Xiongziyan Xiao Hongcheng Huang AAML ObjD 24 4 0 14 Nov 2021
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 19 18 0 29 Oct 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 35 4 0 16 Sep 2021
Improving Visual Quality of Unrestricted Adversarial Examples with Wavelet-VAE Wenzhao Xiang Chang-rui Liu Shibao Zheng 23 2 0 25 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Saeed Mian Navid Kardan M. Shah AAML 26 235 0 01 Aug 2021
Uncertainty-Aware Reliable Text Classification Yibo Hu Latifur Khan EDL UQCV 33 33 0 15 Jul 2021
Adversarial Examples Make Strong Poisons Liam H. Fowl Micah Goldblum Ping Yeh-Chiang Jonas Geiping Wojtek Czaja Tom Goldstein SILM 23 131 0 21 Jun 2021
Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks Dequan Wang An Ju Evan Shelhamer David A. Wagner Trevor Darrell AAML 26 26 0 18 May 2021
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators David Stutz Nandhini Chandramoorthy Matthias Hein Bernt Schiele AAML MQ 22 18 0 16 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 29 65 0 09 Apr 2021
Adversarial Training is Not Ready for Robot Learning Mathias Lechner Ramin Hasani Radu Grosu Daniela Rus T. Henzinger AAML 38 34 0 15 Mar 2021
Latent Adversarial Debiasing: Mitigating Collider Bias in Deep Neural Networks L. N. Darlow Stanisław Jastrzębski Amos Storkey 48 24 0 19 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 46 8 0 03 Nov 2020
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data Lingkai Kong Haoming Jiang Yuchen Zhuang Jie Lyu T. Zhao Chao Zhang OODD 19 26 0 22 Oct 2020
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning Hongjun Wang Guanbin Li Xiaobai Liu Liang Lin GAN AAML 16 22 0 15 Oct 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks Wei-An Lin Chun Pong Lau Alexander Levine Ramalingam Chellappa S. Feizi AAML 81 60 0 05 Sep 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 27 147 0 20 May 2020
Spanning Attack: Reinforce Black-box Attacks with Unlabeled Data Lu Wang Huan Zhang Jinfeng Yi Cho-Jui Hsieh Yuan Jiang AAML 27 12 0 11 May 2020
Adversarial Training against Location-Optimized Adversarial Patches Sukrut Rao David Stutz Bernt Schiele AAML 11 91 0 05 May 2020
Towards Feature Space Adversarial Attack Qiuling Xu Guanhong Tao Shuyang Cheng Xinming Zhang GAN AAML 25 25 0 26 Apr 2020
Learning to Learn Single Domain Generalization Fengchun Qiao Long Zhao Xi Peng OOD 31 431 0 30 Mar 2020