Generating Less Certain Adversarial Examples Improves Robust Generalization

6 October 2023

Papers citing "Generating Less Certain Adversarial Examples Improves Robust Generalization"

49 / 49 papers shown

Title
CTBENCH: A Library and Benchmark for Certified Training Yuhao Mao Stefan Balauca Martin Vechev OOD 89 5 0 07 Jun 2024
CFA: Class-wise Calibrated Fair Adversarial Training Zeming Wei Yifei Wang Yiwen Guo Yisen Wang AAML 80 53 0 25 Mar 2023
Escaping limit cycles: Global convergence for constrained nonconvex-nonconcave minimax problems Thomas Pethick P. Latafat Panagiotis Patrinos Olivier Fercoq Volkan Cevher 76 47 0 20 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min Lin Weiwei Liu Shuicheng Yan DiffM 54 223 0 09 Feb 2023
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness Yuancheng Xu Yanchao Sun Micah Goldblum Tom Goldstein Furong Huang AAML 63 38 0 06 Feb 2023
Understanding Robust Overfitting of Adversarial Training and Beyond Chaojian Yu Bo Han Li Shen Jun Yu Chen Gong Biwei Huang Tongliang Liu OOD 69 60 0 17 Jun 2022
Adversarial Unlearning: Reducing Confidence Along Adversarial Directions Amrith Rajagopal Setlur Benjamin Eysenbach Virginia Smith Sergey Levine 55 18 0 03 Jun 2022
Enhancing Adversarial Training with Second-Order Statistics of Weights Gao Jin Xinping Yi Wei Huang S. Schewe Xiaowei Huang AAML 73 47 0 11 Mar 2022
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 84 66 0 09 Apr 2021
Consistency Regularization for Adversarial Robustness Jihoon Tack Sihyun Yu Jongheon Jeong Minseon Kim Sung Ju Hwang Jinwoo Shin AAML 68 61 0 08 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 81 272 0 02 Mar 2021
Efficient Methods for Structured Nonconvex-Nonconcave Min-Max Optimization Jelena Diakonikolas C. Daskalakis Michael I. Jordan 70 144 0 31 Oct 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 322 702 0 19 Oct 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 57 11 0 21 Sep 2020
Understanding and Improving Fast Adversarial Training Maksym Andriushchenko Nicolas Flammarion AAML 79 290 0 06 Jul 2020
The limits of min-max optimization algorithms: convergence to spurious non-critical sets Ya-Ping Hsieh P. Mertikopoulos Volkan Cevher 74 83 0 16 Jun 2020
Reevaluating Adversarial Examples in Natural Language John X. Morris Eli Lifland Jack Lanchantin Yangfeng Ji Yanjun Qi SILM AAML 173 114 0 25 Apr 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 216 1,846 0 03 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 99 801 0 26 Feb 2020
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality Yi Zhang Orestis Plevrakis S. Du Xingguo Li Zhao Song Sanjeev Arora 108 52 0 16 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 138 1,178 0 12 Jan 2020
AdvHat: Real-world adversarial attack on ArcFace Face ID system Stepan Alekseevich Komkov Aleksandr Petiushko AAML CVBM 54 285 0 23 Aug 2019
Convergence of Gradient Methods on Bilinear Zero-Sum Games Guojun Zhang Yaoliang Yu 47 37 0 15 Aug 2019
Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems Xingjun Ma Yuhao Niu Lin Gu Yisen Wang Yitian Zhao James Bailey Feng Lu MedIm AAML 69 451 0 24 Jul 2019
Convergence of Adversarial Training in Overparametrized Neural Networks Ruiqi Gao Tianle Cai Haochuan Li Liwei Wang Cho-Jui Hsieh Jason D. Lee AAML 96 109 0 19 Jun 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 125 752 0 31 May 2019
Are Labels Required for Improving Adversarial Robustness? J. Uesato Jean-Baptiste Alayrac Po-Sen Huang Robert Stanforth Alhussein Fawzi Pushmeet Kohli AAML 74 333 0 31 May 2019
Adversarial Examples Are Not Bugs, They Are Features Andrew Ilyas Shibani Santurkar Dimitris Tsipras Logan Engstrom Brandon Tran Aleksander Madry SILM 89 1,838 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 130 1,247 0 29 Apr 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 150 2,039 0 08 Feb 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 134 2,551 0 24 Jan 2019
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu Laurens van der Maaten Alan Yuille Kaiming He 107 909 0 09 Dec 2018
Theoretical Analysis of Adversarial Learning: A Minimax Approach Zhuozhuo Tu Jingwei Zhang Dacheng Tao AAML 45 68 0 13 Nov 2018
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 94,891 0 11 Oct 2018
The Limit Points of (Optimistic) Gradient Descent in Min-Max Optimization C. Daskalakis Ioannis Panageas 69 256 0 11 Jul 2018
Optimistic mirror descent in saddle-point problems: Going the extra (gradient) mile P. Mertikopoulos Bruno Lecouat Houssam Zenati Chuan-Sheng Foo V. Chandrasekhar Georgios Piliouras 132 295 0 07 Jul 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 102 1,781 0 30 May 2018
On the Suitability of $L_p$ -norms for Creating and Preventing Adversarial Examples Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 125 138 0 27 Feb 2018
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality Xingjun Ma Yue Liu Yisen Wang S. Erfani S. Wijewickrema Grant Schoenebeck D. Song Michael E. Houle James Bailey AAML 111 739 0 08 Jan 2018
Spatially Transformed Adversarial Examples Chaowei Xiao Jun-Yan Zhu Yue Liu Warren He M. Liu D. Song AAML 74 523 0 08 Jan 2018
Geometric robustness of deep networks: analysis and improvement Can Kanbak Seyed-Mohsen Moosavi-Dezfooli P. Frossard OOD AAML 84 131 0 24 Nov 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 307 12,069 0 19 Jun 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 177 2,725 0 19 May 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 264 8,552 0 16 Aug 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,020 0 10 Dec 2015
Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks Nicolas Papernot Patrick McDaniel Xi Wu S. Jha A. Swami AAML 102 3,072 0 14 Nov 2015
DeepDriving: Learning Affordance for Direct Perception in Autonomous Driving Chenyi Chen Ari Seff A. Kornhauser Jianxiong Xiao 99 1,765 0 01 May 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,066 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 270 14,927 1 21 Dec 2013