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
Fast Propagation is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetworks Xiaojun Jia Jianshu Li Jindong Gu Yang Bai Xiaochun Cao AAML 22 9 0 24 Oct 2023
A Novel Information-Theoretic Objective to Disentangle Representations for Fair Classification Pierre Colombo Nathan Noiry Guillaume Staerman Pablo Piantanida FaML DRL 28 1 0 21 Oct 2023
OODRobustBench: a Benchmark and Large-Scale Analysis of Adversarial Robustness under Distribution Shift Lin Li Yifei Wang Chawin Sitawarin Michael W. Spratling 24 0 0 19 Oct 2023
Learn from the Past: A Proxy Guided Adversarial Defense Framework with Self Distillation Regularization Yaohua Liu Jiaxin Gao Xianghao Jiao Zhu Liu Xin-Yue Fan Risheng Liu AAML 35 0 0 19 Oct 2023
IRAD: Implicit Representation-driven Image Resampling against Adversarial Attacks Yue Cao Tianlin Li Xiaofeng Cao Ivor Tsang Yang Liu Qing-Wu Guo AAML 21 2 0 18 Oct 2023
Towards Deep Learning Models Resistant to Transfer-based Adversarial Attacks via Data-centric Robust Learning Yulong Yang Chenhao Lin Xiang Ji Qiwei Tian Qian Li Hongshan Yang Zhibo Wang Chao Shen 22 7 0 15 Oct 2023
AFLOW: Developing Adversarial Examples under Extremely Noise-limited Settings Renyang Liu Jinhong Zhang Haoran Li Jin Zhang Yuanyu Wang Wei Zhou AAML 19 3 0 15 Oct 2023
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting Runqi Lin Chaojian Yu Bo Han Tongliang Liu 17 7 0 13 Oct 2023
A Geometrical Approach to Evaluate the Adversarial Robustness of Deep Neural Networks Yang Wang B. Dong Ke Xu Haiyin Piao Yufei Ding Baocai Yin Xin Yang AAML 26 3 0 10 Oct 2023
Generating Less Certain Adversarial Examples Improves Robust Generalization Minxing Zhang Michael Backes Xiao Zhang AAML 40 1 0 06 Oct 2023
SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks Alexander Robey Eric Wong Hamed Hassani George J. Pappas AAML 38 215 0 05 Oct 2023
Splitting the Difference on Adversarial Training Matan Levi A. Kontorovich 32 4 0 03 Oct 2023
Intrinsic Biologically Plausible Adversarial Robustness Matilde Tristany Farinha Thomas Ortner Giorgia Dellaferrera Benjamin Grewe A. Pantazi AAML 30 1 0 29 Sep 2023
Adversarial Examples Might be Avoidable: The Role of Data Concentration in Adversarial Robustness Ambar Pal Huaijin Hao René Vidal 26 8 0 28 Sep 2023
Structure Invariant Transformation for better Adversarial Transferability Xiaosen Wang Zeliang Zhang Jianping Zhang AAML 22 59 0 26 Sep 2023
Language Guided Adversarial Purification Himanshu Singh A. V. Subramanyam AAML 41 2 0 19 Sep 2023
Reducing Adversarial Training Cost with Gradient Approximation Huihui Gong AAML 6 0 0 18 Sep 2023
Deep Nonparametric Convexified Filtering for Computational Photography, Image Synthesis and Adversarial Defense Jianqiao Wangni 14 0 0 13 Sep 2023
RobustEdge: Low Power Adversarial Detection for Cloud-Edge Systems Abhishek Moitra Abhiroop Bhattacharjee Youngeun Kim Priyadarshini Panda AAML 19 1 0 05 Sep 2023
Hindering Adversarial Attacks with Multiple Encrypted Patch Embeddings AprilPyone Maungmaung Isao Echizen Hitoshi Kiya AAML 21 2 0 04 Sep 2023
Robust and Efficient Interference Neural Networks for Defending Against Adversarial Attacks in ImageNet Yunuo Xiong Shujuan Liu H. Xiong AAML 27 0 0 03 Sep 2023
Towards Certified Probabilistic Robustness with High Accuracy Ruihan Zhang Peixin Zhang Jun Sun AAML 19 0 0 02 Sep 2023
Robust Principles: Architectural Design Principles for Adversarially Robust CNNs Sheng-Hsuan Peng Weilin Xu Cory Cornelius Matthew Hull Kevin Li Rahul Duggal Mansi Phute Jason Martin Duen Horng Chau AAML 13 46 0 30 Aug 2023
DiffSmooth: Certifiably Robust Learning via Diffusion Models and Local Smoothing Jiawei Zhang Zhongzhu Chen Huan Zhang Chaowei Xiao Bo-wen Li DiffM 31 21 0 28 Aug 2023
Fast Adversarial Training with Smooth Convergence Mengnan Zhao L. Zhang Yuqiu Kong Baocai Yin AAML 22 8 0 24 Aug 2023
Revisiting and Exploring Efficient Fast Adversarial Training via LAW: Lipschitz Regularization and Auto Weight Averaging Xiaojun Jia YueFeng Chen Xiaofeng Mao Ranjie Duan Jindong Gu Rong Zhang H. Xue Xiaochun Cao AAML 11 9 0 22 Aug 2023
Enhancing Adversarial Attacks: The Similar Target Method Shuo Zhang Ziruo Wang Zikai Zhou Huanran Chen AAML 46 1 0 21 Aug 2023
Adversarial Collaborative Filtering for Free Huiyuan Chen Xiaoting Li Vivian Lai Chin-Chia Michael Yeh Yujie Fan Yan Zheng Mahashweta Das Hao Yang AAML 15 6 0 20 Aug 2023
Robust Mixture-of-Expert Training for Convolutional Neural Networks Yihua Zhang Ruisi Cai Tianlong Chen Guanhua Zhang Huan Zhang Pin-Yu Chen Shiyu Chang Zhangyang Wang Sijia Liu MoE AAML OOD 30 16 0 19 Aug 2023
On the Interplay of Convolutional Padding and Adversarial Robustness Paul Gavrikov J. Keuper AAML 23 3 0 12 Aug 2023
Not So Robust After All: Evaluating the Robustness of Deep Neural Networks to Unseen Adversarial Attacks R. Garaev Bader Rasheed Adil Mehmood Khan AAML OOD 20 1 0 12 Aug 2023
Non-Convex Bilevel Optimization with Time-Varying Objective Functions Sen-Fon Lin Daouda Sow Kaiyi Ji Yitao Liang Ness B. Shroff 31 2 0 07 Aug 2023
FROD: Robust Object Detection for Free Muhammad Awais Awais Weiming Zhuang Zhuang Lingjuan Lingjuan Lyu Sung-Ho Sung-Ho Bae ObjD 21 1 0 03 Aug 2023
Hard Adversarial Example Mining for Improving Robust Fairness Chenhao Lin Xiang Ji Yulong Yang Q. Li Chao Shen Run Wang Liming Fang AAML 22 2 0 03 Aug 2023
Training on Foveated Images Improves Robustness to Adversarial Attacks Muhammad Ahmed Shah Bhiksha Raj AAML 25 3 0 01 Aug 2023
An Introduction to Bi-level Optimization: Foundations and Applications in Signal Processing and Machine Learning Yihua Zhang Prashant Khanduri Ioannis C. Tsaknakis Yuguang Yao Min-Fong Hong Sijia Liu AI4CE 36 25 0 01 Aug 2023
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness Ruoxi Qin Linyuan Wang Xuehui Du Xing-yuan Chen Binghai Yan AAML 24 0 0 01 Aug 2023
Doubly Robust Instance-Reweighted Adversarial Training Daouda Sow Sen-Fon Lin Zhangyang Wang Yitao Liang AAML OOD 33 2 0 01 Aug 2023
Learning Provably Robust Estimators for Inverse Problems via Jittering Anselm Krainovic Mahdi Soltanolkotabi Reinhard Heckel OOD 22 6 0 24 Jul 2023
HybridAugment++: Unified Frequency Spectra Perturbations for Model Robustness M. K. Yucel R. G. Cinbis Pinar Duygulu AAML 33 10 0 21 Jul 2023
Improving Transferability of Adversarial Examples via Bayesian Attacks Qizhang Li Yiwen Guo Xiaochen Yang W. Zuo Hao Chen AAML BDL 24 2 0 21 Jul 2023
Shared Adversarial Unlearning: Backdoor Mitigation by Unlearning Shared Adversarial Examples Shaokui Wei Mingda Zhang H. Zha Baoyuan Wu TPM 18 34 0 20 Jul 2023
Fix your downsampling ASAP! Be natively more robust via Aliasing and Spectral Artifact free Pooling Julia Grabinski J. Keuper M. Keuper AAML 35 7 0 19 Jul 2023
Towards Building More Robust Models with Frequency Bias Qingwen Bu Dong Huang Heming Cui AAML 15 10 0 19 Jul 2023
Mitigating Adversarial Vulnerability through Causal Parameter Estimation by Adversarial Double Machine Learning Byung-Kwan Lee Junho Kim Yonghyun Ro AAML 10 9 0 14 Jul 2023
Robust Ranking Explanations Chao Chen Chenghua Guo Guixiang Ma Ming Zeng Xi Zhang Sihong Xie FAtt AAML 32 0 0 08 Jul 2023
Group-based Robustness: A General Framework for Customized Robustness in the Real World Weiran Lin Keane Lucas Neo Eyal Lujo Bauer Michael K. Reiter Mahmood Sharif OOD AAML 22 1 0 29 Jun 2023
Advancing Adversarial Training by Injecting Booster Signal Hong Joo Lee Youngjoon Yu Yonghyun Ro AAML 14 3 0 27 Jun 2023
DSRM: Boost Textual Adversarial Training with Distribution Shift Risk Minimization Songyang Gao Shihan Dou Yan Liu Xiao Wang Qi Zhang Zhongyu Wei Jin Ma Yingchun Shan OOD 17 3 0 27 Jun 2023
A Spectral Perspective towards Understanding and Improving Adversarial Robustness Binxiao Huang Rui Lin Chaofan Tao Ngai Wong AAML 40 0 0 25 Jun 2023