You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle

2 May 2019

Tianyuan Zhang

Papers citing "You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle"

50 / 106 papers shown

Title
DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks Shiwen Ni Jiawen Li Hung-Yu kao AAML 19 4 0 29 Aug 2021
ASAT: Adaptively Scaled Adversarial Training in Time Series Zhiyuan Zhang Wei Li Ruihan Bao Keiko Harimoto Yunfang Wu Xu Sun AI4TS 27 5 0 20 Aug 2021
A Survey on Data Augmentation for Text Classification Markus Bayer M. Kaufhold Christian A. Reuter 38 336 0 07 Jul 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 11 12 0 14 Jun 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
Concurrent Adversarial Learning for Large-Batch Training Yong Liu Xiangning Chen Minhao Cheng Cho-Jui Hsieh Yang You ODL 33 13 0 01 Jun 2021
NoiLIn: Improving Adversarial Training and Correcting Stereotype of Noisy Labels Jingfeng Zhang Xilie Xu Bo Han Tongliang Liu Gang Niu Li-zhen Cui Masashi Sugiyama NoLa AAML 23 9 0 31 May 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
LAFEAT: Piercing Through Adversarial Defenses with Latent Features Yunrui Yu Xitong Gao Chengzhong Xu AAML FedML 33 44 0 19 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 36 65 0 09 Apr 2021
Universal Adversarial Training with Class-Wise Perturbations Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 22 26 0 07 Apr 2021
Adversarial Robustness under Long-Tailed Distribution Tong Wu Ziwei Liu Qingqiu Huang Yu Wang Dahua Lin 21 76 0 06 Apr 2021
Learning Defense Transformers for Counterattacking Adversarial Examples Jincheng Li Jingyun Liang Yifan Zhang Jian Chen Mingkui Tan AAML 37 2 0 13 Mar 2021
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack Mengting Xu Tao Zhang Zhongnian Li Mingxia Liu Daoqiang Zhang AAML OOD MedIm 33 41 0 05 Mar 2021
Dynamic Efficient Adversarial Training Guided by Gradient Magnitude Fu Lee Wang Yanghao Zhang Yanbin Zheng Wenjie Ruan 28 1 0 04 Mar 2021
A Survey On Universal Adversarial Attack Chaoning Zhang Philipp Benz Chenguo Lin Adil Karjauv Jing Wu In So Kweon AAML 23 90 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 21 47 0 20 Feb 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 32 45 0 15 Feb 2021
Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead Maurizio Capra Beatrice Bussolino Alberto Marchisio Guido Masera Maurizio Martina Muhammad Shafique BDL 59 140 0 21 Dec 2020
ROBY: Evaluating the Robustness of a Deep Model by its Decision Boundaries Jinyin Chen Zhen Wang Haibin Zheng Jun Xiao Zhaoyan Ming AAML 19 5 0 18 Dec 2020
Improving Adversarial Robustness via Probabilistically Compact Loss with Logit Constraints X. Li Xiangrui Li Deng Pan D. Zhu AAML 21 17 0 14 Dec 2020
Learnable Boundary Guided Adversarial Training Jiequan Cui Shu Liu Liwei Wang Jiaya Jia OOD AAML 30 124 0 23 Nov 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 49 8 0 03 Nov 2020
Robustness May Be at Odds with Fairness: An Empirical Study on Class-wise Accuracy Philipp Benz Chaoning Zhang Adil Karjauv In So Kweon AAML 24 57 0 26 Oct 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 27 26 0 22 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 234 680 0 19 Oct 2020
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning Hongjun Wang Guanbin Li Xiaobai Liu Liang Lin GAN AAML 21 22 0 15 Oct 2020
A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation Dinghan Shen Ming Zheng Yelong Shen Yanru Qu Weizhu Chen AAML 29 130 0 29 Sep 2020
Practical Detection of Trojan Neural Networks: Data-Limited and Data-Free Cases Ren Wang Gaoyuan Zhang Sijia Liu Pin-Yu Chen Jinjun Xiong Meng Wang AAML 33 148 0 31 Jul 2020
A Differential Game Theoretic Neural Optimizer for Training Residual Networks Guan-Horng Liu T. Chen Evangelos A. Theodorou 24 2 0 17 Jul 2020
Odyssey: Creation, Analysis and Detection of Trojan Models Marzieh Edraki Nazmul Karim Nazanin Rahnavard Ajmal Mian M. Shah AAML 28 13 0 16 Jul 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 24 81 0 15 Jun 2020
Large-Scale Adversarial Training for Vision-and-Language Representation Learning Zhe Gan Yen-Chun Chen Linjie Li Chen Zhu Yu Cheng Jingjing Liu ObjD VLM 35 488 0 11 Jun 2020
A Stochastic Subgradient Method for Distributionally Robust Non-Convex Learning Mert Gurbuzbalaban A. Ruszczynski Landi Zhu 26 9 0 08 Jun 2020
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses Yaxin Li Wei Jin Han Xu Jiliang Tang AAML 32 131 0 13 May 2020
Robust Deep Learning as Optimal Control: Insights and Convergence Guarantees Jacob H. Seidman Mahyar Fazlyab V. Preciado George J. Pappas AAML 16 15 0 01 May 2020
Diversity can be Transferred: Output Diversification for White- and Black-box Attacks Y. Tashiro Yang Song Stefano Ermon AAML 14 13 0 15 Mar 2020
A Mean-field Analysis of Deep ResNet and Beyond: Towards Provable Optimization Via Overparameterization From Depth Yiping Lu Chao Ma Yulong Lu Jianfeng Lu Lexing Ying MLT 39 78 0 11 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 47 787 0 26 Feb 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger Jingfeng Zhang Xilie Xu Bo Han Gang Niu Li-zhen Cui Masashi Sugiyama Mohan S. Kankanhalli AAML 33 397 0 26 Feb 2020
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization Yifei Min Lin Chen Amin Karbasi AAML 37 69 0 25 Feb 2020
Black-Box Certification with Randomized Smoothing: A Functional Optimization Based Framework Dinghuai Zhang Mao Ye Chengyue Gong Zhanxing Zhu Qiang Liu AAML 24 62 0 21 Feb 2020
CAT: Customized Adversarial Training for Improved Robustness Minhao Cheng Qi Lei Pin-Yu Chen Inderjit Dhillon Cho-Jui Hsieh OOD AAML 27 114 0 17 Feb 2020
Semantic Robustness of Models of Source Code Goutham Ramakrishnan Jordan Henkel Zi Wang Aws Albarghouthi S. Jha Thomas W. Reps SILM AAML 47 97 0 07 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 99 1,159 0 12 Jan 2020
MACER: Attack-free and Scalable Robust Training via Maximizing Certified Radius Runtian Zhai Chen Dan Di He Huan Zhang Boqing Gong Pradeep Ravikumar Cho-Jui Hsieh Liwei Wang OOD AAML 16 177 0 08 Jan 2020
Efficient Adversarial Training with Transferable Adversarial Examples Haizhong Zheng Ziqi Zhang Juncheng Gu Honglak Lee A. Prakash AAML 24 108 0 27 Dec 2019
Deep Learning via Dynamical Systems: An Approximation Perspective Qianxiao Li Ting Lin Zuowei Shen AI4TS AI4CE 25 107 0 22 Dec 2019
A Review on Deep Learning in Medical Image Reconstruction Hai-Miao Zhang Bin Dong MedIm 35 122 0 23 Jun 2019
Intriguing properties of adversarial training at scale Cihang Xie Alan Yuille AAML 13 68 0 10 Jun 2019