Adversarial Examples Are Not Bugs, They Are Features

6 May 2019

Papers citing "Adversarial Examples Are Not Bugs, They Are Features"

50 / 306 papers shown

Title
GreedyFool: Multi-Factor Imperceptibility and Its Application to Designing a Black-box Adversarial Attack Hui Liu Bo Zhao Minzhi Ji Peng Liu AAML 27 6 0 14 Oct 2020
A Unified Approach to Interpreting and Boosting Adversarial Transferability Xin Eric Wang Jie Ren Shuyu Lin Xiangming Zhu Yisen Wang Quanshi Zhang AAML 26 94 0 08 Oct 2020
Generating End-to-End Adversarial Examples for Malware Classifiers Using Explainability Ishai Rosenberg Shai Meir J. Berrebi I. Gordon Guillaume Sicard Eli David AAML SILM 9 25 0 28 Sep 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 19 11 0 21 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 33 62 0 11 Sep 2020
Dual Manifold Adversarial Robustness: Defense against Lp and non-Lp Adversarial Attacks Wei-An Lin Chun Pong Lau Alexander Levine Ramalingam Chellappa S. Feizi AAML 81 60 0 05 Sep 2020
A Wholistic View of Continual Learning with Deep Neural Networks: Forgotten Lessons and the Bridge to Active and Open World Learning Martin Mundt Yongjun Hong Iuliia Pliushch Visvanathan Ramesh CLL 27 146 0 03 Sep 2020
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 19 19 0 19 Aug 2020
Optimizing Information Loss Towards Robust Neural Networks Philip Sperl Konstantin Böttinger AAML 13 3 0 07 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 25 73 0 07 Aug 2020
When is invariance useful in an Out-of-Distribution Generalization problem ? Masanori Koyama Shoichiro Yamaguchi OOD 31 65 0 04 Aug 2020
Robust and Generalizable Visual Representation Learning via Random Convolutions Zhenlin Xu Deyi Liu Junlin Yang Colin Raffel Marc Niethammer OOD AAML 49 189 0 25 Jul 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 19 23 0 22 Jul 2020
Do Adversarially Robust ImageNet Models Transfer Better? Hadi Salman Andrew Ilyas Logan Engstrom Ashish Kapoor A. Madry 34 416 0 16 Jul 2020
Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency Robert Geirhos Kristof Meding Felix Wichmann 13 116 0 30 Jun 2020
Adversarial Self-Supervised Contrastive Learning Minseon Kim Jihoon Tack Sung Ju Hwang SSL 20 246 0 13 Jun 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 27 146 0 20 May 2020
Blind Backdoors in Deep Learning Models Eugene Bagdasaryan Vitaly Shmatikov AAML FedML SILM 24 298 0 08 May 2020
Towards Frequency-Based Explanation for Robust CNN Zifan Wang Yilin Yang Ankit Shrivastava Varun Rawal Zihao Ding AAML FAtt 13 47 0 06 May 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 26 8 0 23 Apr 2020
M2m: Imbalanced Classification via Major-to-minor Translation Jaehyung Kim Jongheon Jeong Jinwoo Shin 13 220 0 01 Apr 2020
Going in circles is the way forward: the role of recurrence in visual inference R. S. V. Bergen N. Kriegeskorte 17 81 0 26 Mar 2020
ARAE: Adversarially Robust Training of Autoencoders Improves Novelty Detection Mohammadreza Salehi Atrin Arya Barbod Pajoum Mohammad Otoofi Amirreza Shaeiri M. Rohban Hamid R. Rabiee AAML 26 62 0 12 Mar 2020
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization Saehyung Lee Hyungyu Lee Sungroh Yoon AAML 161 113 0 05 Mar 2020
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 Mar 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 22 396 0 26 Feb 2020
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization Yifei Min Lin Chen Amin Karbasi AAML 31 69 0 25 Feb 2020
Gödel's Sentence Is An Adversarial Example But Unsolvable Xiaodong Qi Lansheng Han AAML 20 0 0 25 Feb 2020
CEB Improves Model Robustness Ian S. Fischer Alexander A. Alemi AAML 17 28 0 13 Feb 2020
The Conditional Entropy Bottleneck Ian S. Fischer OOD 19 115 0 13 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 27 64 0 11 Feb 2020
Efficient Adversarial Training with Transferable Adversarial Examples Haizhong Zheng Ziqi Zhang Juncheng Gu Honglak Lee A. Prakash AAML 22 107 0 27 Dec 2019
Label-Consistent Backdoor Attacks Alexander Turner Dimitris Tsipras A. Madry AAML 11 383 0 05 Dec 2019
AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds Abdullah Hamdi Sara Rojas Ali K. Thabet Bernard Ghanem AAML 3DPC 25 127 0 01 Dec 2019
Universal adversarial examples in speech command classification Jon Vadillo Roberto Santana AAML 29 29 0 22 Nov 2019
Defective Convolutional Networks Tiange Luo Tianle Cai Mengxiao Zhang Siyu Chen Di He Liwei Wang AAML 22 3 0 19 Nov 2019
Adversarial Examples in Modern Machine Learning: A Review R. Wiyatno Anqi Xu Ousmane Amadou Dia A. D. Berker AAML 13 103 0 13 Nov 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks Rémi Bernhard Pierre-Alain Moëllic J. Dutertre AAML MQ 24 18 0 27 Sep 2019
When Explainability Meets Adversarial Learning: Detecting Adversarial Examples using SHAP Signatures Gil Fidel Ron Bitton A. Shabtai FAtt GAN 18 119 0 08 Sep 2019
Adversarial shape perturbations on 3D point clouds Daniel Liu Ronald Yu Hao Su 3DPC 27 12 0 16 Aug 2019
Imperio: Robust Over-the-Air Adversarial Examples for Automatic Speech Recognition Systems Lea Schonherr Thorsten Eisenhofer Steffen Zeiler Thorsten Holz D. Kolossa AAML 41 63 0 05 Aug 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 21 230 0 24 Jul 2019
Improving performance of deep learning models with axiomatic attribution priors and expected gradients G. Erion Joseph D. Janizek Pascal Sturmfels Scott M. Lundberg Su-In Lee OOD BDL FAtt 13 80 0 25 Jun 2019
Intriguing properties of adversarial training at scale Cihang Xie Alan Yuille AAML 8 68 0 10 Jun 2019
Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation Raphael Gontijo-Lopes Dong Yin Ben Poole Justin Gilmer E. D. Cubuk AAML 30 204 0 06 Jun 2019
Adversarial Robustness as a Prior for Learned Representations Logan Engstrom Andrew Ilyas Shibani Santurkar Dimitris Tsipras Brandon Tran A. Madry OOD AAML 16 63 0 03 Jun 2019
The Principle of Unchanged Optimality in Reinforcement Learning Generalization A. Irpan Xingyou Song OffRL 25 7 0 02 Jun 2019
Adversarial Policies: Attacking Deep Reinforcement Learning Adam Gleave Michael Dennis Cody Wild Neel Kant Sergey Levine Stuart J. Russell AAML 27 348 0 25 May 2019
Zero-shot Knowledge Transfer via Adversarial Belief Matching P. Micaelli Amos Storkey 17 227 0 23 May 2019
Adversarial Training and Robustness for Multiple Perturbations Florian Tramèr Dan Boneh AAML SILM 19 374 0 30 Apr 2019