Understanding and Combating Robust Overfitting via Input Loss Landscape Analysis and Regularization

9 December 2022

Papers citing "Understanding and Combating Robust Overfitting via Input Loss Landscape Analysis and Regularization"

8 / 8 papers shown

Title
Are Classification Robustness and Explanation Robustness Really Strongly Correlated? An Analysis Through Input Loss Landscape Tiejin Chen Wenwang Huang Linsey Pang Dongsheng Luo Hua Wei OOD 49 0 0 09 Mar 2024
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
Improving Fast Adversarial Training with Prior-Guided Knowledge Xiaojun Jia Yong Zhang Xingxing Wei Baoyuan Wu Ke Ma Jue Wang Xiaochun Cao AAML 34 26 0 01 Apr 2023
Certified Robust Neural Networks: Generalization and Corruption Resistance Amine Bennouna Ryan Lucas Bart P. G. Van Parys 38 10 0 03 Mar 2023
Data Augmentation Alone Can Improve Adversarial Training Lin Li Michael W. Spratling 16 50 0 24 Jan 2023
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
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 291 3,110 0 04 Nov 2016
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 296 39,198 0 01 Sep 2014