Improving Adversarial Robustness via Promoting Ensemble Diversity

25 January 2019

Kun Xu

Jun Zhu

Papers citing "Improving Adversarial Robustness via Promoting Ensemble Diversity"

50 / 63 papers shown

Title
Two is Better than One: Efficient Ensemble Defense for Robust and Compact Models Yoojin Jung Byung Cheol Song AAML VLM MQ 36 0 0 07 Apr 2025
A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications Siyuan Mu Sen Lin MoE 129 1 0 10 Mar 2025
TAET: Two-Stage Adversarial Equalization Training on Long-Tailed Distributions Wang YuHang Junkang Guo Aolei Liu Kaihao Wang Zaitong Wu Zhenyu Liu Wenfei Yin Jian Liu AAML 50 0 0 02 Mar 2025
Quantifying Correlations of Machine Learning Models Yuanyuan Li Neeraj Sarna Yang Lin 83 0 0 06 Feb 2025
LookHere: Vision Transformers with Directed Attention Generalize and Extrapolate A. Fuller Daniel G. Kyrollos Yousef Yassin James R. Green 46 2 0 22 May 2024
A Random Ensemble of Encrypted Vision Transformers for Adversarially Robust Defense Ryota Iijima Sayaka Shiota Hitoshi Kiya 30 6 0 11 Feb 2024
Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance Wenqi Wei Ling Liu 25 16 0 02 Feb 2024
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off Yatong Bai Brendon G. Anderson Somayeh Sojoudi AAML 22 2 0 26 Nov 2023
PubDef: Defending Against Transfer Attacks From Public Models Chawin Sitawarin Jaewon Chang David Huang Wesson Altoyan David A. Wagner AAML 31 5 0 26 Oct 2023
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks Yang Wang B. Dong Ke Xu Haiyin Piao Yufei Ding Baocai Yin Xin Yang AAML 31 3 0 10 Oct 2023
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness Ruoxi Qin Linyuan Wang Xuehui Du Xing-yuan Chen Binghai Yan AAML 26 0 0 01 Aug 2023
Diversifying Deep Ensembles: A Saliency Map Approach for Enhanced OOD Detection, Calibration, and Accuracy Stanislav Dereka I. Karpukhin Maksim Zhdanov Sergey Kolesnikov 33 0 0 19 May 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 21 208 0 09 Feb 2023
On the Robustness of Randomized Ensembles to Adversarial Perturbations Hassan Dbouk Naresh R Shanbhag AAML 23 7 0 02 Feb 2023
Pathologies of Predictive Diversity in Deep Ensembles Taiga Abe E. Kelly Buchanan Geoff Pleiss John P. Cunningham UQCV 38 13 0 01 Feb 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 30 18 0 29 Jan 2023
A Unified Theory of Diversity in Ensemble Learning Danny Wood Tingting Mu Andrew M. Webb Henry W. J. Reeve M. Luján Gavin Brown UQCV 20 41 0 10 Jan 2023
Game Theoretic Mixed Experts for Combinational Adversarial Machine Learning Ethan Rathbun Kaleel Mahmood Sohaib Ahmad Caiwen Ding Marten van Dijk AAML 19 4 0 26 Nov 2022
Adversarial Detection by Approximation of Ensemble Boundary T. Windeatt AAML 24 0 0 18 Nov 2022
Saliency Guided Adversarial Training for Learning Generalizable Features with Applications to Medical Imaging Classification System Xin Li Yao Qiang Chengyin Li Sijia Liu D. Zhu OOD MedIm 29 4 0 09 Sep 2022
Building Robust Ensembles via Margin Boosting Dinghuai Zhang Hongyang R. Zhang Aaron Courville Yoshua Bengio Pradeep Ravikumar A. Suggala AAML UQCV 40 15 0 07 Jun 2022
Diverse Lottery Tickets Boost Ensemble from a Single Pretrained Model Sosuke Kobayashi Shun Kiyono Jun Suzuki Kentaro Inui MoMe 23 7 0 24 May 2022
Towards efficient feature sharing in MIMO architectures Rémy Sun Alexandre Ramé Clément Masson Nicolas Thome Matthieu Cord 62 6 0 20 May 2022
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 49 71 0 26 Mar 2022
Self-Ensemble Adversarial Training for Improved Robustness Hongjun Wang Yisen Wang OOD AAML 11 48 0 18 Mar 2022
3D Common Corruptions and Data Augmentation Oğuzhan Fatih Kar Teresa Yeo Andrei Atanov Amir Zamir 3DPC 35 107 0 02 Mar 2022
A Unified Wasserstein Distributional Robustness Framework for Adversarial Training Tu Bui Trung Le Quan Hung Tran He Zhao Dinh Q. Phung AAML OOD 31 42 0 27 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
On the Impact of Hard Adversarial Instances on Overfitting in Adversarial Training Chen Liu Zhichao Huang Mathieu Salzmann Tong Zhang Sabine Süsstrunk AAML 15 13 0 14 Dec 2021
Push Stricter to Decide Better: A Class-Conditional Feature Adaptive Framework for Improving Adversarial Robustness Jia-Li Yin Lehui Xie Wanqing Zhu Ximeng Liu Bo-Hao Chen TTA AAML 19 3 0 01 Dec 2021
Adaptive Perturbation for Adversarial Attack Zheng Yuan Jie M. Zhang Zhaoyan Jiang Liangliang Li Shiguang Shan AAML 21 3 0 27 Nov 2021
Data Augmentation Can Improve Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 17 269 0 09 Nov 2021
Adversarial defenses via a mixture of generators Maciej Żelaszczyk Jacek Mañdziuk AAML 11 0 0 05 Oct 2021
Introducing the DOME Activation Functions Mohamed E. Hussein Wael AbdAlmageed 25 1 0 30 Sep 2021
Impact of Attention on Adversarial Robustness of Image Classification Models Prachi Agrawal Narinder Singh Punn S. K. Sonbhadra Sonali Agarwal AAML 16 6 0 02 Sep 2021
Regional Adversarial Training for Better Robust Generalization Chuanbiao Song Yanbo Fan Yichen Yang Baoyuan Wu Yiming Li Zhifeng Li Kun He AAML OOD 11 6 0 02 Sep 2021
Meta Gradient Adversarial Attack Zheng Yuan Jie M. Zhang Yunpei Jia Chuanqi Tan Tao Xue Shiguang Shan AAML 49 78 0 09 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
On the Certified Robustness for Ensemble Models and Beyond Zhuolin Yang Linyi Li Xiaojun Xu B. Kailkhura Tao Xie Bo-wen Li AAML 13 48 0 22 Jul 2021
Conformal Anomaly Detection on Spatio-Temporal Observations with Missing Data Chen Xu Yao Xie 24 20 0 25 May 2021
Evading the Simplicity Bias: Training a Diverse Set of Models Discovers Solutions with Superior OOD Generalization Damien Teney Ehsan Abbasnejad Simon Lucey A. Hengel 23 86 0 12 May 2021
On the Robustness of Vision Transformers to Adversarial Examples Kaleel Mahmood Rigel Mahmood Marten van Dijk ViT 20 217 0 31 Mar 2021
Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness Yi Cai Xuefei Ning Huazhong Yang Yu Wang AAML 25 4 0 27 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 27 268 0 02 Mar 2021
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning Ren Wang Kaidi Xu Sijia Liu Pin-Yu Chen Tsui-Wei Weng Chuang Gan Meng Wang AAML 11 46 0 20 Feb 2021
Guided Interpolation for Adversarial Training Chen Chen Jingfeng Zhang Xilie Xu Tianlei Hu Gang Niu Gang Chen Masashi Sugiyama AAML 19 10 0 15 Feb 2021
DICE: Diversity in Deep Ensembles via Conditional Redundancy Adversarial Estimation Alexandre Ramé Matthieu Cord FedML 45 51 0 14 Jan 2021
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 17 323 0 07 Oct 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 19 11 0 21 Sep 2020
Adversarially Robust Neural Architectures Minjing Dong Yanxi Li Yunhe Wang Chang Xu AAML OOD 34 48 0 02 Sep 2020