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
Towards quantum enhanced adversarial robustness in machine learning Maxwell T. West S. Tsang J. S. Low C. Hill C. Leckie Lloyd C. L. Hollenberg S. Erfani Muhammad Usman AAML OOD 16 53 0 22 Jun 2023
Adversarial Training Should Be Cast as a Non-Zero-Sum Game Alexander Robey Fabian Latorre George J. Pappas Hamed Hassani V. Cevher AAML 66 12 0 19 Jun 2023
Finite Gaussian Neurons: Defending against adversarial attacks by making neural networks say "I don't know" Félix Grèzes AAML 6 0 0 13 Jun 2023
Revisiting and Advancing Adversarial Training Through A Simple Baseline Hong Liu AAML 24 0 0 13 Jun 2023
AROID: Improving Adversarial Robustness through Online Instance-wise Data Augmentation Lin Li Jianing Qiu Michael W. Spratling AAML 30 4 0 12 Jun 2023
NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial Perturbations Y. Fu Ye Yuan Souvik Kundu Shang Wu Shunyao Zhang Yingyan Lin AAML 60 6 0 10 Jun 2023
Generalizable Lightweight Proxy for Robust NAS against Diverse Perturbations Hyeonjeong Ha Minseon Kim S. Hwang OOD AAML 25 5 0 08 Jun 2023
Enhance Diffusion to Improve Robust Generalization Jianhui Sun Sanchit Sinha Aidong Zhang 24 4 0 05 Jun 2023
A Closer Look at the Adversarial Robustness of Deep Equilibrium Models Zonghan Yang Tianyu Pang Yang Liu AAML 11 14 0 02 Jun 2023
Towards Understanding Clean Generalization and Robust Overfitting in Adversarial Training Binghui Li Yuanzhi Li AAML 26 3 0 02 Jun 2023
Amplification trojan network: Attack deep neural networks by amplifying their inherent weakness Zhan Hu Jun Zhu Bo Zhang Xiaolin Hu AAML 19 2 0 28 May 2023
Detecting Adversarial Data by Probing Multiple Perturbations Using Expected Perturbation Score Shuhai Zhang Feng Liu Jiahao Yang Yifan Yang Changsheng Li Bo Han Mingkui Tan DiffM AAML 26 17 0 25 May 2023
PEARL: Preprocessing Enhanced Adversarial Robust Learning of Image Deraining for Semantic Segmentation Xianghao Jiao Yao-Tsorng Liu Jiaxin Gao Xinyuan Chu Risheng Liu Xin-Yue Fan VLM 24 6 0 25 May 2023
Robust Classification via a Single Diffusion Model Huanran Chen Yinpeng Dong Zhengyi Wang X. Yang Chen-Dong Duan Hang Su Jun Zhu 74 56 0 24 May 2023
Introducing Competition to Boost the Transferability of Targeted Adversarial Examples through Clean Feature Mixup Junyoung Byun Myung-Joon Kwon Seungju Cho Yoonji Kim Changick Kim AAML 17 17 0 24 May 2023
Expressive Losses for Verified Robustness via Convex Combinations Alessandro De Palma Rudy Bunel Krishnamurthy Dvijotham M. P. Kumar Robert Stanforth A. Lomuscio AAML 33 11 0 23 May 2023
Adversarial Defenses via Vector Quantization Zhiyi Dong Yongyi Mao AAML 11 1 0 23 May 2023
Regularization Through Simultaneous Learning: A Case Study on Plant Classification Pedro Henrique Nascimento Castro Gabriel Cássia Fortuna Rafael Alves Bonfim de Queiroz Gladston J. P. Moreira Eduardo José da S. Luz 13 0 0 22 May 2023
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation Xiaowei Huang Wenjie Ruan Wei Huang Gao Jin Yizhen Dong ... Sihao Wu Peipei Xu Dengyu Wu André Freitas Mustafa A. Mustafa ALM 29 81 0 19 May 2023
How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses Joana Cabral Costa Tiago Roxo Hugo Manuel Proença Pedro R. M. Inácio AAML 34 49 0 18 May 2023
Unlearnable Examples Give a False Sense of Security: Piercing through Unexploitable Data with Learnable Examples Wanzhu Jiang Yunfeng Diao He-Nan Wang Jianxin Sun M. Wang Richang Hong 37 18 0 16 May 2023
Exploiting Frequency Spectrum of Adversarial Images for General Robustness Chun Yang Tan K. Kawamoto Hiroshi Kera AAML OOD 26 1 0 15 May 2023
Toward Adversarial Training on Contextualized Language Representation Hongqiu Wu Y. Liu Han Shi Haizhen Zhao M. Zhang AAML 15 13 0 08 May 2023
Rethinking Graph Lottery Tickets: Graph Sparsity Matters Bo Hui Jocelyn M Mora Adrian V. Dalca I. Aganj 37 22 0 03 May 2023
Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks Jingfeng Zhang Bo Song Bo Han Lei Liu Gang Niu Masashi Sugiyama AAML 11 2 0 30 Apr 2023
Adversary Aware Continual Learning Muhammad Umer R. Polikar AAML 17 2 0 27 Apr 2023
Concept-Monitor: Understanding DNN training through individual neurons Mohammad Ali Khan Tuomas P. Oikarinen Tsui-Wei Weng 21 2 0 26 Apr 2023
Generating Adversarial Examples with Task Oriented Multi-Objective Optimization Anh-Vu Bui Trung Le He Zhao Quan Hung Tran Paul Montague Dinh Q. Phung AAML 34 0 0 26 Apr 2023
Combining Adversaries with Anti-adversaries in Training Xiaoling Zhou Nan Yang Ou Wu AAML 10 6 0 25 Apr 2023
Certified Adversarial Robustness Within Multiple Perturbation Bounds Soumalya Nandi Sravanti Addepalli Harsh Rangwani R. Venkatesh Babu AAML 11 3 0 20 Apr 2023
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models Zaitang Li Pin-Yu Chen Tsung-Yi Ho AAML DiffM 30 4 0 19 Apr 2023
Wavelets Beat Monkeys at Adversarial Robustness Jingtong Su Julia Kempe AAML OOD 22 2 0 19 Apr 2023
OOD-CV-v2: An extended Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images Bingchen Zhao Jiahao Wang Wufei Ma Artur Jesslen Si-Jia Yang Shaozuo Yu O. Zendel Christian Theobalt Alan Yuille Adam Kortylewski 29 8 0 17 Apr 2023
Cross-Entropy Loss Functions: Theoretical Analysis and Applications Anqi Mao M. Mohri Yutao Zhong AAML 21 273 0 14 Apr 2023
Unsupervised Multi-Criteria Adversarial Detection in Deep Image Retrieval Yanru Xiao Cong Wang Xing Gao AAML 11 0 0 09 Apr 2023
Robust Deep Learning Models Against Semantic-Preserving Adversarial Attack Dashan Gao Yunce Zhao Yinghua Yao Zeqi Zhang Bifei Mao Xin Yao AAML 28 0 0 08 Apr 2023
A Certified Radius-Guided Attack Framework to Image Segmentation Models Wenjie Qu Youqi Li Binghui Wang AAML 13 5 0 05 Apr 2023
Hyper-parameter Tuning for Adversarially Robust Models Pedro Mendes Paolo Romano David Garlan AAML 11 2 0 05 Apr 2023
Improving Fast Adversarial Training with Prior-Guided Knowledge Xiaojun Jia Yong Zhang Xingxing Wei Baoyuan Wu Ke Ma Jue Wang Xiaochun Cao AAML 21 26 0 01 Apr 2023
To be Robust and to be Fair: Aligning Fairness with Robustness Junyi Chai Xiaoqian Wang 41 2 0 31 Mar 2023
Generating Adversarial Samples in Mini-Batches May Be Detrimental To Adversarial Robustness T. Redgrave Colton R. Crum AAML 18 0 0 30 Mar 2023
Improving the Transferability of Adversarial Examples via Direction Tuning Xiangyuan Yang Jie Lin Hanlin Zhang Xinyu Yang Peng Zhao AAML 27 12 0 27 Mar 2023
Decentralized Adversarial Training over Graphs Ying Cao Elsa Rizk Stefan Vlaski A. H. Sayed AAML 35 1 0 23 Mar 2023
Reliable and Efficient Evaluation of Adversarial Robustness for Deep Hashing-Based Retrieval Xunguang Wang Jiawang Bai Xin-Chao Xu X. Li AAML 8 1 0 22 Mar 2023
PRISE: Demystifying Deep Lucas-Kanade with Strongly Star-Convex Constraints for Multimodel Image Alignment Yiqing Zhang Xinming Huang Ziming Zhang 34 4 0 21 Mar 2023
Fuzziness-tuned: Improving the Transferability of Adversarial Examples Xiangyuan Yang Jie Lin Hanlin Zhang Xinyu Yang Peng Zhao AAML 27 0 0 17 Mar 2023
Class Attribute Inference Attacks: Inferring Sensitive Class Information by Diffusion-Based Attribute Manipulations Lukas Struppek Dominik Hintersdorf Felix Friedrich Manuel Brack P. Schramowski Kristian Kersting MIACV 25 2 0 16 Mar 2023
Rethinking Model Ensemble in Transfer-based Adversarial Attacks Huanran Chen Yichi Zhang Yinpeng Dong Xiao Yang Hang Su Junyi Zhu AAML 26 55 0 16 Mar 2023
Robust Evaluation of Diffusion-Based Adversarial Purification M. Lee Dongwoo Kim 34 53 0 16 Mar 2023
Can Adversarial Examples Be Parsed to Reveal Victim Model Information? Yuguang Yao Jiancheng Liu Yifan Gong Xiaoming Liu Yanzhi Wang X. Lin Sijia Liu AAML MLAU 24 1 0 13 Mar 2023