MMA Training: Direct Input Space Margin Maximization through Adversarial Training

6 December 2018

Papers citing "MMA Training: Direct Input Space Margin Maximization through Adversarial Training"

50 / 69 papers shown

Title
Dynamic Guidance Adversarial Distillation with Enhanced Teacher Knowledge Hyejin Park Dongbo Min AAML 42 2 0 03 Sep 2024
A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classification Lu Zhang S. Lambotharan G. Zheng G. Liao Ambra Demontis Fabio Roli AAML 26 10 0 09 Jul 2024
Detecting Brittle Decisions for Free: Leveraging Margin Consistency in Deep Robust Classifiers Jonas Ngnawé Sabyasachi Sahoo Y. Pequignot Frédéric Precioso Christian Gagné AAML 42 0 0 26 Jun 2024
Purify++: Improving Diffusion-Purification with Advanced Diffusion Models and Control of Randomness Boya Zhang Weijian Luo Zhihua Zhang 34 10 0 28 Oct 2023
Tailoring Adversarial Attacks on Deep Neural Networks for Targeted Class Manipulation Using DeepFool Algorithm S. M. Fazle J. Mondal Meem Arafat Manab Xi Xiao Sarfaraz Newaz AAML 29 0 0 18 Oct 2023
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization Mahyar Fazlyab Taha Entesari Aniket Roy Ramalingam Chellappa AAML 16 11 0 29 Sep 2023
Certified Robust Models with Slack Control and Large Lipschitz Constants M. Losch David Stutz Bernt Schiele Mario Fritz 14 4 0 12 Sep 2023
Understanding the robustness difference between stochastic gradient descent and adaptive gradient methods A. Ma Yangchen Pan Amir-massoud Farahmand AAML 25 5 0 13 Aug 2023
Doubly Robust Instance-Reweighted Adversarial Training Daouda Sow Sen-Fon Lin Zhangyang Wang Yitao Liang AAML OOD 33 2 0 01 Aug 2023
Enhancing Adversarial Robustness via Score-Based Optimization Boya Zhang Weijian Luo Zhihua Zhang DiffM 32 13 0 10 Jul 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 42 1 0 29 Jun 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 44 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 38 34 0 19 Feb 2023
A Data-Centric Approach for Improving Adversarial Training Through the Lens of Out-of-Distribution Detection Mohammad Azizmalayeri Arman Zarei Alireza Isavand M. T. Manzuri M. Rohban OODD 35 0 0 25 Jan 2023
Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization Zifa Wang Nan Ding Tomer Levinboim Xi Chen Radu Soricut AAML 35 5 0 22 Nov 2022
Impact of Adversarial Training on Robustness and Generalizability of Language Models Enes Altinisik Hassan Sajjad Husrev Taha Sencar Safa Messaoud Sanjay Chawla AAML 24 8 0 10 Nov 2022
Adversarial Defense via Neural Oscillation inspired Gradient Masking Chunming Jiang Yilei Zhang AAML 29 2 0 04 Nov 2022
Scoring Black-Box Models for Adversarial Robustness Jian Vora Pranay Reddy Samala 33 0 0 31 Oct 2022
Learning Sample Reweighting for Accuracy and Adversarial Robustness Chester Holtz Tsui-Wei Weng Gal Mishne OOD 33 4 0 20 Oct 2022
Effective Targeted Attacks for Adversarial Self-Supervised Learning Minseon Kim Hyeonjeong Ha Sooel Son Sung Ju Hwang AAML 39 3 0 19 Oct 2022
Robust Models are less Over-Confident Julia Grabinski Paul Gavrikov J. Keuper M. Keuper AAML 36 24 0 12 Oct 2022
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization Ziquan Liu Antoni B. Chan AAML 33 5 0 11 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
Queried Unlabeled Data Improves and Robustifies Class-Incremental Learning Tianlong Chen Sijia Liu Shiyu Chang Lisa Amini Zhangyang Wang CLL 26 4 0 15 Jun 2022
Diffusion Models for Adversarial Purification Weili Nie Brandon Guo Yujia Huang Chaowei Xiao Arash Vahdat Anima Anandkumar WIGM 218 419 0 16 May 2022
CE-based white-box adversarial attacks will not work using super-fitting Youhuan Yang Lei Sun Leyu Dai Song Guo Xiuqing Mao Xiaoqin Wang Bayi Xu AAML 37 0 0 04 May 2022
Adversarial Robustness through the Lens of Convolutional Filters Paul Gavrikov J. Keuper 38 15 0 05 Apr 2022
CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters Paul Gavrikov J. Keuper AAML 24 31 0 29 Mar 2022
Self-Ensemble Adversarial Training for Improved Robustness Hongjun Wang Yisen Wang OOD AAML 13 48 0 18 Mar 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 29 47 0 11 Mar 2022
Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack Ye Liu Yaya Cheng Lianli Gao Xianglong Liu Qilong Zhang Jingkuan Song AAML 37 57 0 10 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 Lin Xiao Yang Junyi Zhu Shuicheng Yan 30 119 0 21 Feb 2022
Generalized Strategic Classification and the Case of Aligned Incentives Sagi Levanon Nir Rosenfeld 24 26 0 09 Feb 2022
Boundary Defense Against Black-box Adversarial Attacks Manjushree B. Aithal Xiaohua Li AAML 21 6 0 31 Jan 2022
Improving Robustness by Enhancing Weak Subnets Yong Guo David Stutz Bernt Schiele AAML 27 15 0 30 Jan 2022
Constrained Gradient Descent: A Powerful and Principled Evasion Attack Against Neural Networks Weiran Lin Keane Lucas Lujo Bauer Michael K. Reiter Mahmood Sharif AAML 31 5 0 28 Dec 2021
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 209 345 0 15 Dec 2021
Understanding Square Loss in Training Overparametrized Neural Network Classifiers Tianyang Hu Jun Wang Wei Cao Zhenguo Li UQCV AAML 41 19 0 07 Dec 2021
Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness Ke Sun Mingjie Li Zhouchen Lin AAML 27 2 0 03 Nov 2021
Meta-Learning the Search Distribution of Black-Box Random Search Based Adversarial Attacks Maksym Yatsura J. H. Metzen Matthias Hein OOD 26 14 0 02 Nov 2021
Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Hanxun Huang Yisen Wang S. Erfani Quanquan Gu James Bailey Xingjun Ma AAML TPM 46 100 0 07 Oct 2021
Label Noise in Adversarial Training: A Novel Perspective to Study Robust Overfitting Chengyu Dong Liyuan Liu Jingbo Shang NoLa AAML 61 18 0 07 Oct 2021
Calibrated Adversarial Training Tianjin Huang Vlado Menkovski Yulong Pei Mykola Pechenizkiy AAML 56 3 0 01 Oct 2021
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining Weizhe Hua Yichi Zhang Chuan Guo Zhiru Zhang G. E. Suh OOD 39 15 0 29 Sep 2021
AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric Learning Hong Wang Yuefan Deng Shinjae Yoo Haibin Ling Yuewei Lin AAML 32 15 0 13 Aug 2021
Advances in adversarial attacks and defenses in computer vision: A survey Naveed Akhtar Ajmal Mian Navid Kardan M. Shah AAML 31 236 0 01 Aug 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients Alessandro Cappelli Julien Launay Laurent Meunier Ruben Ohana Iacopo Poli AAML 24 4 0 06 Jul 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 21 31 0 09 Jun 2021
Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks Leo Schwinn René Raab A. Nguyen Dario Zanca Bjoern M. Eskofier AAML 14 60 0 21 May 2021