Fast is better than free: Revisiting adversarial training

12 January 2020

J. Zico Kolter

Papers citing "Fast is better than free: Revisiting adversarial training"

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Title
Toward Degradation-Robust Voice Conversion Chien-yu Huang Kai-Wei Chang Hung-yi Lee 25 7 0 14 Oct 2021
Model-Agnostic Meta-Attack: Towards Reliable Evaluation of Adversarial Robustness Xiao Yang Yinpeng Dong Wenzhao Xiang Tianyu Pang Hang Su Jun Zhu AAML 21 4 0 13 Oct 2021
Boosting Fast Adversarial Training with Learnable Adversarial Initialization Xiaojun Jia Yong Zhang Baoyuan Wu Jue Wang Xiaochun Cao AAML 47 54 0 11 Oct 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
Improving Adversarial Robustness for Free with Snapshot Ensemble Yihao Wang AAML UQCV 17 1 0 07 Oct 2021
Introducing the DOME Activation Functions Mohamed E. Hussein Wael AbdAlmageed 30 1 0 30 Sep 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
Adversarial Transfer Attacks With Unknown Data and Class Overlap Luke E. Richards A. Nguyen Ryan Capps Steven D. Forsythe Cynthia Matuszek Edward Raff AAML 38 7 0 23 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 38 16 0 20 Sep 2021
On the Noise Stability and Robustness of Adversarially Trained Networks on NVM Crossbars Chun Tao Deboleena Roy I. Chakraborty Kaushik Roy AAML 29 2 0 19 Sep 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 35 4 0 16 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 45 10 0 13 Sep 2021
Evolving Architectures with Gradient Misalignment toward Low Adversarial Transferability K. Operiano W. Pora H. Iba Hiroshi Kera AAML 21 1 0 13 Sep 2021
Adversarially Trained Object Detector for Unsupervised Domain Adaptation Kazuma Fujii Hiroshi Kera K. Kawamoto ObjD AAML 23 3 0 13 Sep 2021
2-in-1 Accelerator: Enabling Random Precision Switch for Winning Both Adversarial Robustness and Efficiency Yonggan Fu Yang Katie Zhao Qixuan Yu Chaojian Li Yingyan Lin AAML 49 12 0 11 Sep 2021
Training Meta-Surrogate Model for Transferable Adversarial Attack Yunxiao Qin Yuanhao Xiong Jinfeng Yi Cho-Jui Hsieh AAML 15 18 0 05 Sep 2021
Utilizing Adversarial Targeted Attacks to Boost Adversarial Robustness Uriya Pesso Koby Bibas M. Feder AAML 13 2 0 04 Sep 2021
Adversarial Robustness for Unsupervised Domain Adaptation Muhammad Awais Fengwei Zhou Hang Xu Lanqing Hong Ping Luo Sung-Ho Bae Zhenguo Li 20 39 0 02 Sep 2021
How Does Adversarial Fine-Tuning Benefit BERT? J. Ebrahimi Hao Yang Wei Zhang AAML 26 4 0 31 Aug 2021
Adaptive perturbation adversarial training: based on reinforcement learning Zhi-pin Nie Ying Lin Sp Ren Lan Zhang AAML 20 1 0 30 Aug 2021
Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks N. Mirnateghi Syed Afaq Ali Shah Bennamoun BDL AAML 16 2 0 23 Aug 2021
Towards Understanding the Generative Capability of Adversarially Robust Classifiers Yao Zhu Jiacheng Ma Jiacheng Sun Zewei Chen Rongxin Jiang Zhenguo Li AAML 18 21 0 20 Aug 2021
Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain Guangyao Chen Peixi Peng Li Ma Jia Li Lin Du Yonghong Tian AAML OOD 29 89 0 19 Aug 2021
Neural Architecture Dilation for Adversarial Robustness Yanxi Li Zhaohui Yang Yunhe Wang Chang Xu AAML 38 23 0 16 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
Adversarial training may be a double-edged sword A. Rahmati Seyed-Mohsen Moosavi-Dezfooli H. Dai AAML 31 0 0 24 Jul 2021
An overview of mixing augmentation methods and augmentation strategies Dominik Lewy Jacek Mańdziuk 23 61 0 21 Jul 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 104 196 0 12 Jul 2021
Identifying Layers Susceptible to Adversarial Attacks Shoaib Ahmed Siddiqui Thomas Breuel AAML 16 1 0 10 Jul 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
Single-Step Adversarial Training for Semantic Segmentation D. Wiens Barbara Hammer SSeg AAML 18 1 0 30 Jun 2021
Multi-stage Optimization based Adversarial Training Xiaosen Wang Chuanbiao Song Liwei Wang Kun He AAML 11 5 0 26 Jun 2021
Countering Adversarial Examples: Combining Input Transformation and Noisy Training Cheng Zhang Pan Gao AAML 17 3 0 25 Jun 2021
Fourier Transform Approximation as an Auxiliary Task for Image Classification Chen Liu 27 0 0 22 Jun 2021
Federated Robustness Propagation: Sharing Robustness in Heterogeneous Federated Learning Junyuan Hong Haotao Wang Zhangyang Wang Jiayu Zhou FedML 28 16 0 18 Jun 2021
Adversarial Visual Robustness by Causal Intervention Kaihua Tang Ming Tao Hanwang Zhang CML AAML 27 21 0 17 Jun 2021
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks Yulong Cao* Ningfei Wang* Chaowei Xiao Dawei Yang Jin Fang Ruigang Yang Qi Alfred Chen Mingyan D. Liu Bo-wen Li AAML 24 217 0 17 Jun 2021
DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting Shaoru Chen Eric Wong Zico Kolter Mahyar Fazlyab 47 15 0 16 Jun 2021
Probabilistic Margins for Instance Reweighting in Adversarial Training Qizhou Wang Feng Liu Bo Han Tongliang Liu Chen Gong Gang Niu Mingyuan Zhou Masashi Sugiyama AAML 29 61 0 15 Jun 2021
CARTL: Cooperative Adversarially-Robust Transfer Learning Dian Chen Hongxin Hu Qian Wang Yinli Li Cong Wang Chao Shen Qi Li 15 13 0 12 Jun 2021
CausalAdv: Adversarial Robustness through the Lens of Causality Yonggang Zhang Biwei Huang Tongliang Liu Gang Niu Xinmei Tian Bo Han Bernhard Schölkopf Anton van den Hengel OOD AAML CML 27 35 0 11 Jun 2021
Attacking Adversarial Attacks as A Defense Boxi Wu Heng Pan Li Shen Jindong Gu Shuai Zhao Zhifeng Li Deng Cai Xiaofei He Wei Liu AAML 23 31 0 09 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
Exploring Memorization in Adversarial Training Yinpeng Dong Ke Xu Xiao Yang Tianyu Pang Zhijie Deng Hang Su Jun Zhu TDI 13 69 0 03 Jun 2021
When Vision Transformers Outperform ResNets without Pre-training or Strong Data Augmentations Xiangning Chen Cho-Jui Hsieh Boqing Gong ViT 29 320 0 03 Jun 2021
Exposing Previously Undetectable Faults in Deep Neural Networks Isaac Dunn Hadrien Pouget Daniel Kroening T. Melham AAML 26 28 0 01 Jun 2021
Concurrent Adversarial Learning for Large-Batch Training Yong Liu Xiangning Chen Minhao Cheng Cho-Jui Hsieh Yang You ODL 28 13 0 01 Jun 2021
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart Tianyu Pang Huishuai Zhang Di He Yinpeng Dong Hang Su Wei Chen Jun Zhu Tie-Yan Liu AAML 8 16 0 31 May 2021
A Protection Method of Trained CNN Model with Secret Key from Unauthorized Access AprilPyone Maungmaung Hitoshi Kiya 13 22 0 31 May 2021
$Robustifying $\ell_\infty$ Adversarial Training to the Union of Perturbation Models$ Robustifying $\ell_\infty$ Adversarial Training to the Union of Perturbation Models Ameya D. Patil Michael Tuttle A. Schwing Naresh R Shanbhag AAML 21 0 0 31 May 2021