Adversarial Training for Free!

29 April 2019

Papers citing "Adversarial Training for Free!"

50 / 706 papers shown

Title
Robustness against Adversarial Attacks in Neural Networks using Incremental Dissipativity B. Aquino Arash Rahnama Peter M. Seiler Lizhen Lin Vijay Gupta AAML 30 8 0 25 Nov 2021
Understanding the Dynamics of DNNs Using Graph Modularity Yao Lu Wen Yang Yunzhe Zhang Zuohui Chen Jinyin Chen Qi Xuan Zhen Wang Xiaoniu Yang 42 9 0 24 Nov 2021
Subspace Adversarial Training Tao Li Yingwen Wu Sizhe Chen Kun Fang Xiaolin Huang AAML OOD 44 57 0 24 Nov 2021
Medical Aegis: Robust adversarial protectors for medical images Qingsong Yao Zecheng He S. Kevin Zhou AAML MedIm 30 2 0 22 Nov 2021
Enhanced countering adversarial attacks via input denoising and feature restoring Yanni Li Wenhui Zhang Jiawei Liu Xiaoli Kou Hui Li Jiangtao Cui AAML 33 2 0 19 Nov 2021
A Review of Adversarial Attack and Defense for Classification Methods Yao Li Minhao Cheng Cho-Jui Hsieh T. C. Lee AAML 37 66 0 18 Nov 2021
A Survey on Adversarial Attacks for Malware Analysis Kshitiz Aryal Maanak Gupta Mahmoud Abdelsalam AAML 36 51 0 16 Nov 2021
Are Transformers More Robust Than CNNs? Yutong Bai Jieru Mei Alan Yuille Cihang Xie ViT AAML 195 258 0 10 Nov 2021
MixACM: Mixup-Based Robustness Transfer via Distillation of Activated Channel Maps Muhammad Awais Fengwei Zhou Chuanlong Xie Jiawei Li Sung-Ho Bae Zhenguo Li AAML 43 17 0 09 Nov 2021
Tightening the Approximation Error of Adversarial Risk with Auto Loss Function Search Pengfei Xia Ziqiang Li Bin Li AAML 48 3 0 09 Nov 2021
Robust and Information-theoretically Safe Bias Classifier against Adversarial Attacks Lijia Yu Xiao-Shan Gao AAML 23 5 0 08 Nov 2021
LTD: Low Temperature Distillation for Robust Adversarial Training Erh-Chung Chen Che-Rung Lee AAML 29 26 0 03 Nov 2021
When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning? Lijie Fan Sijia Liu Pin-Yu Chen Gaoyuan Zhang Chuang Gan AAML VLM 22 120 0 01 Nov 2021
Get Fooled for the Right Reason: Improving Adversarial Robustness through a Teacher-guided Curriculum Learning Approach A. Sarkar Anirban Sarkar Sowrya Gali V. Balasubramanian AAML 35 7 0 30 Oct 2021
Adversarial Robustness with Semi-Infinite Constrained Learning Alexander Robey Luiz F. O. Chamon George J. Pappas Hamed Hassani Alejandro Ribeiro AAML OOD 118 43 0 29 Oct 2021
ε-weakened Robustness of Deep Neural Networks Pei Huang Yuting Yang Minghao Liu Fuqi Jia Feifei Ma Jian Zhang AAML 27 18 0 29 Oct 2021
CAP: Co-Adversarial Perturbation on Weights and Features for Improving Generalization of Graph Neural Networks Hao Xue Kaixiong Zhou Tianlong Chen Kai Guo Xia Hu Yi Chang Xin Wang AAML 32 15 0 28 Oct 2021
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks Yonggan Fu Qixuan Yu Yang Zhang Shan-Hung Wu Ouyang Xu David D. Cox Yingyan Lin AAML OOD 33 29 0 26 Oct 2021
Improving Local Effectiveness for Global robust training Jingyue Lu M. P. Kumar AAML 32 0 0 26 Oct 2021
A Frequency Perspective of Adversarial Robustness Shishira R. Maiya Max Ehrlich Vatsal Agarwal Ser-Nam Lim Tom Goldstein Abhinav Shrivastava AAML 23 39 0 26 Oct 2021
Ensemble Federated Adversarial Training with Non-IID data Shuang Luo Didi Zhu Zexi Li Chao-Xiang Wu FedML 33 7 0 26 Oct 2021
A Regularization Method to Improve Adversarial Robustness of Neural Networks for ECG Signal Classification Linhai Ma Liang Liang 17 21 0 19 Oct 2021
Black-box Adversarial Attacks on Commercial Speech Platforms with Minimal Information Baolin Zheng Peipei Jiang Qian Wang Qi Li Chao Shen Cong Wang Yunjie Ge Qingyang Teng Shenyi Zhang AAML 18 69 0 19 Oct 2021
Adversarial Attacks on ML Defense Models Competition Yinpeng Dong Qi-An Fu Xiao Yang Wenzhao Xiang Tianyu Pang ... Zhennan Wu Yang Guo Jiequan Cui Xiaogang Xu Pengguang Chen AAML 18 2 0 15 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 27 4 0 13 Oct 2021
On the Security Risks of AutoML Ren Pang Zhaohan Xi S. Ji Xiapu Luo Ting Wang AAML 27 10 0 12 Oct 2021
Boosting Fast Adversarial Training with Learnable Adversarial Initialization Xiaojun Jia Yong Zhang Baoyuan Wu Jue Wang Xiaochun Cao AAML 50 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 48 100 0 07 Oct 2021
Improving Adversarial Robustness for Free with Snapshot Ensemble Yihao Wang AAML UQCV 17 1 0 07 Oct 2021
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training with Crafted Input Noise Souvik Kundu Massoud Pedram Peter A. Beerel AAML 22 71 0 06 Oct 2021
Generalizing Neural Networks by Reflecting Deviating Data in Production Yan Xiao Yun Lin Ivan Beschastnikh Changsheng Sun David S. Rosenblum Jin Song Dong OOD 16 0 0 06 Oct 2021
BulletTrain: Accelerating Robust Neural Network Training via Boundary Example Mining Weizhe Hua Yichi Zhang Chuan Guo Zhiru Zhang G. E. Suh OOD 44 15 0 29 Sep 2021
Dense Contrastive Visual-Linguistic Pretraining Lei Shi Kai Shuang Shijie Geng Peng Gao Zuohui Fu Gerard de Melo Yunpeng Chen Sen Su VLM SSL 57 10 0 24 Sep 2021
SoK: Machine Learning Governance Varun Chandrasekaran Hengrui Jia Anvith Thudi Adelin Travers Mohammad Yaghini Nicolas Papernot 43 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 37 2 0 19 Sep 2021
Messing Up 3D Virtual Environments: Transferable Adversarial 3D Objects Enrico Meloni Matteo Tiezzi Luca Pasqualini Marco Gori S. Melacci AAML 37 2 0 17 Sep 2021
Simple Post-Training Robustness Using Test Time Augmentations and Random Forest Gilad Cohen Raja Giryes AAML 45 4 0 16 Sep 2021
ARCH: Efficient Adversarial Regularized Training with Caching Simiao Zuo Chen Liang Haoming Jiang Pengcheng He Xiaodong Liu Jianfeng Gao Weizhu Chen T. Zhao AAML 36 3 0 15 Sep 2021
Improving Gradient-based Adversarial Training for Text Classification by Contrastive Learning and Auto-Encoder Yao Qiu Jinchao Zhang Jie Zhou AAML SILM 40 16 0 14 Sep 2021
On the regularized risk of distributionally robust learning over deep neural networks Camilo A. Garcia Trillos Nicolas García Trillos OOD 50 10 0 13 Sep 2021
Evolving Architectures with Gradient Misalignment toward Low Adversarial Transferability K. Operiano W. Pora H. Iba Hiroshi Kera AAML 42 1 0 13 Sep 2021
TREATED:Towards Universal Defense against Textual Adversarial Attacks Bin Zhu Zhaoquan Gu Le Wang Zhihong Tian AAML 36 8 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 52 12 0 11 Sep 2021
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques Shiyu Tang Ruihao Gong Yan Wang Aishan Liu Jiakai Wang ... Xianglong Liu D. Song Alan Yuille Philip Torr Dacheng Tao VLM AAML 26 107 0 11 Sep 2021
Robust fine-tuning of zero-shot models Mitchell Wortsman Gabriel Ilharco Jong Wook Kim Mike Li Simon Kornblith ... Raphael Gontijo-Lopes Hannaneh Hajishirzi Ali Farhadi Hongseok Namkoong Ludwig Schmidt VLM 71 697 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 28 39 0 02 Sep 2021
Real World Robustness from Systematic Noise Yan Wang Yuhang Li Ruihao Gong 36 7 0 02 Sep 2021
DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks Shiwen Ni Jiawen Li Hung-Yu kao AAML 29 4 0 29 Aug 2021
A Hierarchical Assessment of Adversarial Severity Guillaume Jeanneret Juan Pérez Pablo Arbeláez AAML 36 2 0 26 Aug 2021
Deep Bayesian Image Set Classification: A Defence Approach against Adversarial Attacks N. Mirnateghi Syed Afaq Ali Shah Bennamoun BDL AAML 22 2 0 23 Aug 2021