Adversarial Machine Learning at Scale

4 November 2016

Papers citing "Adversarial Machine Learning at Scale"

49 / 1,599 papers shown

Title
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning Hongge Chen Huan Zhang Pin-Yu Chen Jinfeng Yi Cho-Jui Hsieh GAN AAML 35 49 0 06 Dec 2017
Improving Network Robustness against Adversarial Attacks with Compact Convolution Rajeev Ranjan S. Sankaranarayanan Carlos D. Castillo Rama Chellappa AAML 24 14 0 03 Dec 2017
Towards Robust Neural Networks via Random Self-ensemble Xuanqing Liu Minhao Cheng Huan Zhang Cho-Jui Hsieh FedML AAML 58 419 0 02 Dec 2017
Measuring the tendency of CNNs to Learn Surface Statistical Regularities Jason Jo Yoshua Bengio AAML 26 249 0 30 Nov 2017
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 77 1,800 0 30 Nov 2017
On the Robustness of Semantic Segmentation Models to Adversarial Attacks Anurag Arnab O. Mikšík Philip Torr AAML 33 304 0 27 Nov 2017
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients A. Ross Finale Doshi-Velez AAML 37 677 0 26 Nov 2017
Wasserstein Introspective Neural Networks Kwonjoon Lee Weijian Xu Fan Fan Zhuowen Tu 32 57 0 24 Nov 2017
Adversarial Attacks Beyond the Image Space Fangyin Wei Chenxi Liu Yu-Siang Wang Weichao Qiu Lingxi Xie Yu-Wing Tai Chi-Keung Tang Alan Yuille AAML 41 145 0 20 Nov 2017
Enhanced Attacks on Defensively Distilled Deep Neural Networks Yujia Liu Weiming Zhang Shaohua Li Nenghai Yu AAML 13 6 0 16 Nov 2017
Defense against Universal Adversarial Perturbations Naveed Akhtar Jian Liu Ajmal Mian AAML 38 207 0 16 Nov 2017
Machine vs Machine: Minimax-Optimal Defense Against Adversarial Examples Jihun Hamm Akshay Mehra AAML 29 7 0 12 Nov 2017
Crafting Adversarial Examples For Speech Paralinguistics Applications Yuan Gong C. Poellabauer AAML 14 120 0 09 Nov 2017
Intriguing Properties of Adversarial Examples E. D. Cubuk Barret Zoph S. Schoenholz Quoc V. Le AAML 31 84 0 08 Nov 2017
Mitigating Adversarial Effects Through Randomization Cihang Xie Jianyu Wang Zhishuai Zhang Zhou Ren Alan Yuille AAML 23 1,042 0 06 Nov 2017
Attacking Binarized Neural Networks A. Galloway Graham W. Taylor M. Moussa MQ AAML 14 104 0 01 Nov 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 54 1,388 0 31 Oct 2017
Generating Natural Adversarial Examples Zhengli Zhao Dheeru Dua Sameer Singh GAN AAML 40 596 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 54 786 0 30 Oct 2017
Attacking the Madry Defense Model with $L_1$ -based Adversarial Examples Yash Sharma Pin-Yu Chen 17 118 0 30 Oct 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 58 855 0 29 Oct 2017
Boosting Adversarial Attacks with Momentum Yinpeng Dong Fangzhou Liao Tianyu Pang Hang Su Jun Zhu Xiaolin Hu Jianguo Li AAML 26 83 0 17 Oct 2017
Detecting Adversarial Attacks on Neural Network Policies with Visual Foresight Yen-Chen Lin Ming Liu Min Sun Jia-Bin Huang AAML 29 48 0 02 Oct 2017
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks D. Gopinath Guy Katz C. Păsăreanu Clark W. Barrett AAML 50 87 0 02 Oct 2017
Fooling Vision and Language Models Despite Localization and Attention Mechanism Xiaojun Xu Xinyun Chen Chang-rui Liu Anna Rohrbach Trevor Darrell D. Song AAML 10 41 0 25 Sep 2017
Mitigating Evasion Attacks to Deep Neural Networks via Region-based Classification Xiaoyu Cao Neil Zhenqiang Gong AAML 28 208 0 17 Sep 2017
REMOTEGATE: Incentive-Compatible Remote Configuration of Security Gateways Abhinav Aggarwal M. Zamani Mihai Christodorescu 24 0 0 14 Sep 2017
EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples Pin-Yu Chen Yash Sharma Huan Zhang Jinfeng Yi Cho-Jui Hsieh AAML 24 637 0 13 Sep 2017
Towards Interpretable Deep Neural Networks by Leveraging Adversarial Examples Yinpeng Dong Hang Su Jun Zhu Fan Bao AAML 39 128 0 18 Aug 2017
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models Pin-Yu Chen Huan Zhang Yash Sharma Jinfeng Yi Cho-Jui Hsieh AAML 24 1,854 0 14 Aug 2017
Cascade Adversarial Machine Learning Regularized with a Unified Embedding Taesik Na J. Ko Saibal Mukhopadhyay AAML GAN 26 102 0 08 Aug 2017
Adversarial Robustness: Softmax versus Openmax Andras Rozsa Manuel Günther Terrance E. Boult AAML 8 32 0 05 Aug 2017
Fast Feature Fool: A data independent approach to universal adversarial perturbations Konda Reddy Mopuri Utsav Garg R. Venkatesh Babu AAML 38 205 0 18 Jul 2017
UPSET and ANGRI : Breaking High Performance Image Classifiers Sayantan Sarkar Ankan Bansal U. Mahbub Rama Chellappa AAML 30 108 0 04 Jul 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 92 11,884 0 19 Jun 2017
MAT: A Multi-strength Adversarial Training Method to Mitigate Adversarial Attacks Chang Song Hsin-Pai Cheng Huanrui Yang Sicheng Li Chunpeng Wu Qing Wu H. Li Yiran Chen AAML 29 2 0 27 May 2017
Detecting Adversarial Image Examples in Deep Networks with Adaptive Noise Reduction Bin Liang Hongcheng Li Miaoqiang Su Xirong Li Wenchang Shi Xiaofeng Wang AAML 14 216 0 23 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 73 2,701 0 19 May 2017
Parseval Networks: Improving Robustness to Adversarial Examples Moustapha Cissé Piotr Bojanowski Edouard Grave Yann N. Dauphin Nicolas Usunier AAML 86 798 0 28 Apr 2017
Universal Adversarial Perturbations Against Semantic Image Segmentation J. H. Metzen Mummadi Chaithanya Kumar Thomas Brox Volker Fischer AAML 30 287 0 19 Apr 2017
Adversarial and Clean Data Are Not Twins Zhitao Gong Wenlu Wang Wei-Shinn Ku AAML 21 156 0 17 Apr 2017
Adversarial Transformation Networks: Learning to Generate Adversarial Examples S. Baluja Ian S. Fischer GAN 37 284 0 28 Mar 2017
Adversarial Examples for Semantic Segmentation and Object Detection Cihang Xie Jianyu Wang Zhishuai Zhang Yuyin Zhou Lingxi Xie Alan Yuille GAN AAML 37 926 0 24 Mar 2017
Adversarial Attacks on Neural Network Policies Sandy Huang Nicolas Papernot Ian Goodfellow Yan Duan Pieter Abbeel MLAU AAML 13 830 0 08 Feb 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 278 5,695 0 05 Dec 2016
A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Examples Beilun Wang Ji Gao Yanjun Qi AAML 19 30 0 01 Dec 2016
Towards Robust Deep Neural Networks with BANG Andras Rozsa Manuel Günther Terrance E. Boult AAML OOD 24 76 0 01 Dec 2016
LOTS about Attacking Deep Features Andras Rozsa Manuel Günther Terrance E. Boult AAML 48 42 0 18 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 341 5,849 0 08 Jul 2016