Feature Purification: How Adversarial Training Performs Robust Deep Learning

20 May 2020

Papers citing "Feature Purification: How Adversarial Training Performs Robust Deep Learning"

30 / 30 papers shown

Title
Revisiting the Relationship between Adversarial and Clean Training: Why Clean Training Can Make Adversarial Training Better MingWei Zhou Xiaobing Pei AAML 115 0 0 30 Mar 2025
Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning Jingyang Li Jiachun Pan Vincent Y. F. Tan Kim-Chuan Toh Pan Zhou AAML MLT 43 0 0 15 Oct 2024
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data Binghui Li Yuanzhi Li OOD 28 2 0 11 Oct 2024
Feature contamination: Neural networks learn uncorrelated features and fail to generalize Tianren Zhang Chujie Zhao Guanyu Chen Yizhou Jiang Feng Chen OOD MLT OODD 71 3 0 05 Jun 2024
Certifying Adapters: Enabling and Enhancing the Certification of Classifier Adversarial Robustness Jieren Deng Hanbin Hong A. Palmer Xin Zhou Jinbo Bi Kaleel Mahmood Yuan Hong Derek Aguiar AAML 38 0 0 25 May 2024
$How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance$ How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance Hongkang Li Shuai Zhang Yihua Zhang Meng Wang Sijia Liu Pin-Yu Chen 33 4 0 12 Mar 2024
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity Hongkang Li M. Wang Sijia Liu Pin-Yu Chen ViT MLT 35 56 0 12 Feb 2023
Learning threshold neurons via the "edge of stability" Kwangjun Ahn Sébastien Bubeck Sinho Chewi Y. Lee Felipe Suarez Yi Zhang MLT 31 36 0 14 Dec 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 28 12 0 21 Oct 2022
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis Julia Kempe AAML 31 16 0 11 Oct 2022
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization) Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos V. Cevher 39 19 0 15 Sep 2022
Gradient Mask: Lateral Inhibition Mechanism Improves Performance in Artificial Neural Networks Lei Jiang Yongqing Liu Shihai Xiao Yansong Chua 28 0 0 14 Aug 2022
Towards Understanding Mixture of Experts in Deep Learning Zixiang Chen Yihe Deng Yue-bo Wu Quanquan Gu Yuan-Fang Li MLT MoE 21 53 0 04 Aug 2022
GeoECG: Data Augmentation via Wasserstein Geodesic Perturbation for Robust Electrocardiogram Prediction Jiacheng Zhu Jielin Qiu Zhuolin Yang Douglas Weber M. Rosenberg Emerson Liu Bo-wen Li Ding Zhao OOD 28 13 0 02 Aug 2022
Can we achieve robustness from data alone? Nikolaos Tsilivis Jingtong Su Julia Kempe OOD DD 36 18 0 24 Jul 2022
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels Edoardo Cetin Philip J. Ball Steve Roberts Oya Celiktutan 30 36 0 03 Jul 2022
The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning Zixin Wen Yuanzhi Li SSL 19 34 0 12 May 2022
Adversarial robustness of sparse local Lipschitz predictors Ramchandran Muthukumar Jeremias Sulam AAML 32 13 0 26 Feb 2022
Benign Overfitting in Adversarially Robust Linear Classification Jinghui Chen Yuan Cao Quanquan Gu AAML SILM 26 10 0 31 Dec 2021
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 192 345 0 15 Dec 2021
How Does Adversarial Fine-Tuning Benefit BERT? J. Ebrahimi Hao Yang Wei Zhang AAML 18 4 0 31 Aug 2021
Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization Difan Zou Yuan Cao Yuanzhi Li Quanquan Gu MLT AI4CE 39 37 0 25 Aug 2021
Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning Zixin Wen Yuanzhi Li SSL MLT 16 131 0 31 May 2021
A single gradient step finds adversarial examples on random two-layers neural networks Sébastien Bubeck Yeshwanth Cherapanamjeri Gauthier Gidel Rémi Tachet des Combes MLT 26 27 0 08 Apr 2021
Adversarial Training is Not Ready for Robot Learning Mathias Lechner Ramin Hasani Radu Grosu Daniela Rus T. Henzinger AAML 19 34 0 15 Mar 2021
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 19 48 0 19 Oct 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor A. Madry 32 416 0 16 Jul 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 24 8 0 23 Apr 2020
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 186 272 0 03 Dec 2018
Adversarial examples from computational constraints Sébastien Bubeck Eric Price Ilya P. Razenshteyn AAML 62 230 0 25 May 2018