A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies

26 March 2022

Papers citing "A Survey of Robust Adversarial Training in Pattern Recognition: Fundamental, Theory, and Methodologies"

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Title
Learning in High Dimension Always Amounts to Extrapolation Randall Balestriero J. Pesenti Yann LeCun 106 104 0 18 Oct 2021
Improving Model Robustness with Latent Distribution Locally and Globally Zhuang Qian Shufei Zhang Kaizhu Huang Qiufeng Wang Rui Zhang Xinping Yi AAML 38 14 0 08 Jul 2021
Reliably fast adversarial training via latent adversarial perturbation Geon Yeong Park Sang Wan Lee AAML 56 28 0 04 Apr 2021
Understanding and Improving Fast Adversarial Training Maksym Andriushchenko Nicolas Flammarion AAML 68 288 0 06 Jul 2020
RayS: A Ray Searching Method for Hard-label Adversarial Attack Jinghui Chen Quanquan Gu AAML 50 138 0 23 Jun 2020
Towards Robust Pattern Recognition: A Review Xu-Yao Zhang Cheng-Lin Liu C. Suen OOD HAI 52 107 0 12 Jun 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 211 1,837 0 03 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 94 800 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 56 402 0 26 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 61 64 0 11 Feb 2020
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations Florian Tramèr Jens Behrmann Nicholas Carlini Nicolas Papernot J. Jacobsen AAML SILM 38 93 0 11 Feb 2020
Robust Generalization via $α$ -Mutual Information A. Esposito Michael C. Gastpar Ibrahim Issa 36 8 0 14 Jan 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 134 1,175 0 12 Jan 2020
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 73 983 0 29 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 50 105 0 13 Nov 2019
Robust Local Features for Improving the Generalization of Adversarial Training Chuanbiao Song Kun He Jiadong Lin Liwei Wang John E. Hopcroft OOD AAML 41 69 0 23 Sep 2019
Metric Learning for Adversarial Robustness Chengzhi Mao Ziyuan Zhong Junfeng Yang Carl Vondrick Baishakhi Ray OOD 59 185 0 03 Sep 2019
Robust Learning with Jacobian Regularization Judy Hoffman Daniel A. Roberts Sho Yaida OOD AAML 48 167 0 07 Aug 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 59 230 0 24 Jul 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 84 487 0 03 Jul 2019
Adversarially Robust Generalization Just Requires More Unlabeled Data Runtian Zhai Tianle Cai Di He Chen Dan Kun He John E. Hopcroft Liwei Wang 66 156 0 03 Jun 2019
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation Yuzhe Yang Guo Zhang Dina Katabi Zhi Xu AAML 79 170 0 28 May 2019
$Provable robustness against all adversarial $l_p$-perturbations for $p\geq 1$$ Provable robustness against all adversarial $l_p$ -perturbations for $p\geq 1$ Francesco Croce Matthias Hein OOD 49 75 0 27 May 2019
Interpreting Adversarially Trained Convolutional Neural Networks Tianyuan Zhang Zhanxing Zhu AAML GAN FAtt 86 161 0 23 May 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 87 1,836 0 06 May 2019
Adversarial Training for Free! Ali Shafahi Mahyar Najibi Amin Ghiasi Zheng Xu John P. Dickerson Christoph Studer L. Davis Gavin Taylor Tom Goldstein AAML 122 1,242 0 29 Apr 2019
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness J. Jacobsen Jens Behrmann Nicholas Carlini Florian Tramèr Nicolas Papernot AAML 48 46 0 25 Mar 2019
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes Matt Jordan Justin Lewis A. Dimakis AAML 66 57 0 20 Mar 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang Kun Xu Chao Du Ning Chen Jun Zhu AAML 60 437 0 25 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 118 2,542 0 24 Jan 2019
Bilateral Adversarial Training: Towards Fast Training of More Robust Models Against Adversarial Attacks Jianyu Wang Haichao Zhang OOD AAML 77 119 0 26 Nov 2018
Excessive Invariance Causes Adversarial Vulnerability J. Jacobsen Jens Behrmann R. Zemel Matthias Bethge AAML 55 166 0 01 Nov 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 93 1,776 0 30 May 2018
Adversarial Noise Layer: Regularize Neural Network By Adding Noise Zhonghui You Jinmian Ye Kunming Li Zenglin Xu Ping Wang 49 77 0 21 May 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 82 1,176 0 17 May 2018
Adversarially Robust Generalization Requires More Data Ludwig Schmidt Shibani Santurkar Dimitris Tsipras Kunal Talwar Aleksander Madry OOD AAML 131 789 0 30 Apr 2018
Fortified Networks: Improving the Robustness of Deep Networks by Modeling the Manifold of Hidden Representations Alex Lamb Jonathan Binas Anirudh Goyal Dmitriy Serdyuk Sandeep Subramanian Ioannis Mitliagkas Yoshua Bengio OOD 69 43 0 07 Apr 2018
Stochastic Activation Pruning for Robust Adversarial Defense Guneet Singh Dhillon Kamyar Azizzadenesheli Zachary Chase Lipton Jeremy Bernstein Jean Kossaifi Aran Khanna Anima Anandkumar AAML 62 546 0 05 Mar 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 185 3,180 0 01 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 76 467 0 31 Jan 2018
Spatially Transformed Adversarial Examples Chaowei Xiao Jun-Yan Zhu Yue Liu Warren He M. Liu D. Song AAML 70 522 0 08 Jan 2018
Generating Adversarial Examples with Adversarial Networks Chaowei Xiao Yue Liu Jun-Yan Zhu Warren He M. Liu D. Song GAN AAML 115 896 0 08 Jan 2018
Adversarial Examples: Attacks and Defenses for Deep Learning Xiaoyong Yuan Pan He Qile Zhu Xiaolin Li SILM AAML 86 1,618 0 19 Dec 2017
Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models Wieland Brendel Jonas Rauber Matthias Bethge AAML 65 1,342 0 12 Dec 2017
Mitigating Adversarial Effects Through Randomization Cihang Xie Jianyu Wang Zhishuai Zhang Zhou Ren Alan Yuille AAML 99 1,054 0 06 Nov 2017
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 90 1,498 0 02 Nov 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 102 1,400 0 31 Oct 2017
Generating Natural Adversarial Examples Zhengli Zhao Dheeru Dua Sameer Singh GAN AAML 158 599 0 31 Oct 2017
One pixel attack for fooling deep neural networks Jiawei Su Danilo Vasconcellos Vargas Kouichi Sakurai AAML 109 2,320 0 24 Oct 2017
Mixed Precision Training Paulius Micikevicius Sharan Narang Jonah Alben G. Diamos Erich Elsen ... Boris Ginsburg Michael Houston Oleksii Kuchaiev Ganesh Venkatesh Hao Wu 149 1,792 0 10 Oct 2017