Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks

18 May 2021

Papers citing "Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks"

50 / 59 papers shown

Title
Online Adversarial Purification based on Self-Supervision Changhao Shi Chester Holtz Zhengchao Wan AAML 51 57 0 23 Jan 2021
Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer Jian Liang Dapeng Hu Yunbo Wang Ran He Jiashi Feng 186 255 0 14 Dec 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 320 702 0 19 Oct 2020
Improving robustness against common corruptions by covariate shift adaptation Steffen Schneider E. Rusak L. Eck Oliver Bringmann Wieland Brendel Matthias Bethge VLM 92 481 0 30 Jun 2020
Tent: Fully Test-time Adaptation by Entropy Minimization Dequan Wang Evan Shelhamer Shaoteng Liu Bruno A. Olshausen Trevor Darrell OOD 71 53 0 18 Jun 2020
Stochastic Security: Adversarial Defense Using Long-Run Dynamics of Energy-Based Models Mitch Hill Jonathan Mitchell Song-Chun Zhu AAML 55 70 0 27 May 2020
Designing Network Design Spaces Ilija Radosavovic Raj Prateek Kosaraju Ross B. Girshick Kaiming He Piotr Dollár GNN 100 1,682 0 30 Mar 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 216 1,842 0 03 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 97 801 0 26 Feb 2020
Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation Jian Liang Dapeng Hu Jiashi Feng 97 1,241 0 20 Feb 2020
On Adaptive Attacks to Adversarial Example Defenses Florian Tramèr Nicholas Carlini Wieland Brendel Aleksander Madry AAML 274 833 0 19 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
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 493 42,407 0 03 Dec 2019
Square Attack: a query-efficient black-box adversarial attack via random search Maksym Andriushchenko Francesco Croce Nicolas Flammarion Matthias Hein AAML 83 987 0 29 Nov 2019
An Adaptive and Momental Bound Method for Stochastic Learning Jianbang Ding Xuancheng Ren Ruixuan Luo Xu Sun ODL 45 47 0 27 Oct 2019
Test-Time Training with Self-Supervision for Generalization under Distribution Shifts Yu Sun Xiaolong Wang Zhuang Liu John Miller Alexei A. Efros Moritz Hardt TTA OOD 82 94 0 29 Sep 2019
Mixup Inference: Better Exploiting Mixup to Defend Adversarial Attacks Tianyu Pang Kun Xu Jun Zhu AAML 73 105 0 25 Sep 2019
Open Compound Domain Adaptation Ziwei Liu Zhongqi Miao Xingang Pan Xiaohang Zhan Dahua Lin Stella X. Yu Boqing Gong 77 131 0 08 Sep 2019
Deep Equilibrium Models Shaojie Bai J. Zico Kolter V. Koltun 92 665 0 03 Sep 2019
Minimally distorted Adversarial Examples with a Fast Adaptive Boundary Attack Francesco Croce Matthias Hein AAML 87 488 0 03 Jul 2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Yue Liu Duane S. Boning Cho-Jui Hsieh AAML 67 347 0 14 Jun 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 121 752 0 31 May 2019
On Network Design Spaces for Visual Recognition Ilija Radosavovic Justin Johnson Saining Xie Wan-Yen Lo Piotr Dollár 72 135 0 30 May 2019
Adversarial Training and Robustness for Multiple Perturbations Florian Tramèr Dan Boneh AAML SILM 70 378 0 30 Apr 2019
Blurring the Line Between Structure and Learning to Optimize and Adapt Receptive Fields Evan Shelhamer Dequan Wang Trevor Darrell 65 35 0 25 Apr 2019
CondConv: Conditionally Parameterized Convolutions for Efficient Inference Brandon Yang Gabriel Bender Quoc V. Le Jiquan Ngiam MedIm 3DV 70 635 0 10 Apr 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 172 3,431 0 28 Mar 2019
A Research Agenda: Dynamic Models to Defend Against Correlated Attacks Ian Goodfellow AAML OOD 71 31 0 14 Mar 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 147 2,039 0 08 Feb 2019
Adversarial Examples Are a Natural Consequence of Test Error in Noise Nic Ford Justin Gilmer Nicholas Carlini E. D. Cubuk AAML 88 319 0 29 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 134 2,549 0 24 Jan 2019
MMA Training: Direct Input Space Margin Maximization through Adversarial Training G. Ding Yash Sharma Kry Yik-Chau Lui Ruitong Huang AAML 65 273 0 06 Dec 2018
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 263 280 0 03 Dec 2018
Decoupling Direction and Norm for Efficient Gradient-Based L2 Adversarial Attacks and Defenses Jérôme Rony L. G. Hafemann Luiz Eduardo Soares de Oliveira Ismail Ben Ayed R. Sabourin Eric Granger AAML 54 298 0 23 Nov 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models D. Su Huan Zhang Hongge Chen Jinfeng Yi Pin-Yu Chen Yupeng Gao VLM 123 391 0 05 Aug 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 414 5,103 0 19 Jun 2018
Defense-GAN: Protecting Classifiers Against Adversarial Attacks Using Generative Models Pouya Samangouei Maya Kabkab Rama Chellappa AAML GAN 84 1,177 0 17 May 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 78 547 0 05 Mar 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 219 3,185 0 01 Feb 2018
Adversarial Examples: Attacks and Defenses for Deep Learning Xiaoyong Yuan Pan He Qile Zhu Xiaolin Li SILM AAML 88 1,622 0 19 Dec 2017
TensorFlow-Serving: Flexible, High-Performance ML Serving Christopher Olston Noah Fiedel Kiril Gorovoy Jeremiah Harmsen Li Lao Fangwei Li Vinu Rajashekhar Sukriti Ramesh Jordan Soyke 51 306 0 17 Dec 2017
Convolutional Networks with Adaptive Inference Graphs Andreas Veit Serge J. Belongie OOD GNN 93 385 0 30 Nov 2017
SkipNet: Learning Dynamic Routing in Convolutional Networks Xin Wang Feng Yu Zi-Yi Dou Trevor Darrell Joseph E. Gonzalez 101 636 0 26 Nov 2017
CyCADA: Cycle-Consistent Adversarial Domain Adaptation Judy Hoffman Eric Tzeng Taesung Park Jun-Yan Zhu Phillip Isola Kate Saenko Alexei A. Efros Trevor Darrell 142 3,000 0 08 Nov 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 112 1,404 0 31 Oct 2017
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples Yang Song Taesup Kim Sebastian Nowozin Stefano Ermon Nate Kushman AAML 110 791 0 30 Oct 2017
Attacking the Madry Defense Model with $L_1$ -based Adversarial Examples Yash Sharma Pin-Yu Chen 88 118 0 30 Oct 2017
FiLM: Visual Reasoning with a General Conditioning Layer Ethan Perez Florian Strub H. D. Vries Vincent Dumoulin Aaron Courville FAtt AIMat OffRL AI4CE 352 2,208 0 22 Sep 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 304 12,063 0 19 Jun 2017
Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer Noam M. Shazeer Azalia Mirhoseini Krzysztof Maziarz Andy Davis Quoc V. Le Geoffrey E. Hinton J. Dean MoE 248 2,644 0 23 Jan 2017