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Adversarial Machine Learning at Scale

4 November 2016

Papers citing "Adversarial Machine Learning at Scale"

50 / 1,610 papers shown

Title
Scaling provable adversarial defenses Eric Wong Frank R. Schmidt J. H. Metzen J. Zico Kolter AAML 105 450 0 31 May 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 118 1,786 0 30 May 2018
Robustifying Models Against Adversarial Attacks by Langevin Dynamics Vignesh Srinivasan Arturo Marbán K. Müller Wojciech Samek Shinichi Nakajima AAML 78 9 0 30 May 2018
AutoZOOM: Autoencoder-based Zeroth Order Optimization Method for Attacking Black-box Neural Networks Chun-Chen Tu Pai-Shun Ting Pin-Yu Chen Sijia Liu Huan Zhang Jinfeng Yi Cho-Jui Hsieh Shin-Ming Cheng MLAU AAML 94 399 0 30 May 2018
Laplacian Networks: Bounding Indicator Function Smoothness for Neural Network Robustness Carlos Lassance Vincent Gripon Antonio Ortega AAML 88 16 0 24 May 2018
Adversarially Robust Training through Structured Gradient Regularization Kevin Roth Aurelien Lucchi Sebastian Nowozin Thomas Hofmann 72 23 0 22 May 2018
Adversarial Noise Layer: Regularize Neural Network By Adding Noise Zhonghui You Jinmian Ye Kunming Li Zenglin Xu Ping Wang 82 77 0 21 May 2018
Constructing Unrestricted Adversarial Examples with Generative Models Yang Song Rui Shu Nate Kushman Stefano Ermon GAN AAML 222 307 0 21 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 76 41 0 14 May 2018
AttriGuard: A Practical Defense Against Attribute Inference Attacks via Adversarial Machine Learning Jinyuan Jia Neil Zhenqiang Gong AAML 72 166 0 13 May 2018
Curriculum Adversarial Training Qi-Zhi Cai Min Du Chang-rui Liu Basel Alomair AAML 91 165 0 13 May 2018
Formal Security Analysis of Neural Networks using Symbolic Intervals Shiqi Wang Kexin Pei Justin Whitehouse Junfeng Yang Suman Jana AAML 88 478 0 28 Apr 2018
Towards Fast Computation of Certified Robustness for ReLU Networks Tsui-Wei Weng Huan Zhang Hongge Chen Zhao Song Cho-Jui Hsieh Duane S. Boning Inderjit S. Dhillon Luca Daniel AAML 136 696 0 25 Apr 2018
Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning Mahdieh Abbasi Arezoo Rajabi Christian Gagné R. Bobba OODD 61 6 0 24 Apr 2018
VectorDefense: Vectorization as a Defense to Adversarial Examples V. Kabilan Brandon L. Morris Anh Totti Nguyen AAML 66 21 0 23 Apr 2018
Decoupled Networks Weiyang Liu Ziqiang Liu Zhiding Yu Bo Dai Rongmei Lin Yisen Wang James M. Rehg Le Song OOD 66 70 0 22 Apr 2018
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 427 935 0 21 Apr 2018
ADef: an Iterative Algorithm to Construct Adversarial Deformations Rima Alaifari Giovanni S. Alberti Tandri Gauksson AAML 110 97 0 20 Apr 2018
Learning More Robust Features with Adversarial Training Shuangtao Li Yuanke Chen Yanlin Peng Lin Bai OOD AAML 69 23 0 20 Apr 2018
Robustness via Deep Low-Rank Representations Amartya Sanyal Varun Kanade Philip Torr P. Dokania OOD 137 17 0 19 Apr 2018
Robust Machine Comprehension Models via Adversarial Training Yicheng Wang Joey Tianyi Zhou AAML 84 117 0 17 Apr 2018
On the Limitation of MagNet Defense against $L_1$ -based Adversarial Examples Pei-Hsuan Lu Pin-Yu Chen Kang-Cheng Chen Chia-Mu Yu AAML 114 19 0 14 Apr 2018
Adversarial Training Versus Weight Decay A. Galloway T. Tanay Graham W. Taylor AAML 70 23 0 10 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 94 43 0 07 Apr 2018
Adversarial Attacks and Defences Competition Alexey Kurakin Ian Goodfellow Samy Bengio Yinpeng Dong Fangzhou Liao ... Junjiajia Long Yerkebulan Berdibekov Takuya Akiba Seiya Tokui Motoki Abe AAML SILM 100 323 0 31 Mar 2018
Security Consideration For Deep Learning-Based Image Forensics Wei Zhao Pengpeng Yang R. Ni Yao-Min Zhao Haorui Wu AAML 35 5 0 29 Mar 2018
Bypassing Feature Squeezing by Increasing Adversary Strength Yash Sharma Pin-Yu Chen AAML 46 34 0 27 Mar 2018
Adversarial Defense based on Structure-to-Signal Autoencoders Joachim Folz Sebastián M. Palacio Jörn Hees Damian Borth Andreas Dengel AAML 71 32 0 21 Mar 2018
Improving Transferability of Adversarial Examples with Input Diversity Cihang Xie Zhishuai Zhang Yuyin Zhou Song Bai Jianyu Wang Zhou Ren Alan Yuille AAML 136 1,133 0 19 Mar 2018
Adversarial Logit Pairing Harini Kannan Alexey Kurakin Ian Goodfellow AAML 103 629 0 16 Mar 2018
Semantic Adversarial Examples Hossein Hosseini Radha Poovendran GAN AAML 108 199 0 16 Mar 2018
Large Margin Deep Networks for Classification Gamaleldin F. Elsayed Dilip Krishnan H. Mobahi Kevin Regan Samy Bengio MQ 88 285 0 15 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 156 508 0 13 Mar 2018
Invisible Mask: Practical Attacks on Face Recognition with Infrared Zhe Zhou Di Tang Wenyuan Xu Weili Han Xiangyu Liu Kehuan Zhang CVBM AAML 68 103 0 13 Mar 2018
Malytics: A Malware Detection Scheme Mahmood Yousefi-Azar Len Hamey Vijay Varadharajan Shiping Chen 61 40 0 09 Mar 2018
Rethinking Feature Distribution for Loss Functions in Image Classification Weitao Wan Yuanyi Zhong Tianpeng Li Jiansheng Chen 80 168 0 08 Mar 2018
Style Memory: Making a Classifier Network Generative R. Wiyatno Jeff Orchard 70 4 0 05 Mar 2018
Neural Networks Should Be Wide Enough to Learn Disconnected Decision Regions Quynh N. Nguyen Mahesh Chandra Mukkamala Matthias Hein MLT 118 56 0 28 Feb 2018
On the Suitability of $L_p$ -norms for Creating and Preventing Adversarial Examples Mahmood Sharif Lujo Bauer Michael K. Reiter AAML 155 138 0 27 Feb 2018
Max-Mahalanobis Linear Discriminant Analysis Networks Tianyu Pang Chao Du Jun Zhu 83 55 0 26 Feb 2018
Sensitivity and Generalization in Neural Networks: an Empirical Study Roman Novak Yasaman Bahri Daniel A. Abolafia Jeffrey Pennington Jascha Narain Sohl-Dickstein AAML 103 443 0 23 Feb 2018
Deep Defense: Training DNNs with Improved Adversarial Robustness Ziang Yan Yiwen Guo Changshui Zhang AAML 97 110 0 23 Feb 2018
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans Gamaleldin F. Elsayed Shreya Shankar Brian Cheung Nicolas Papernot Alexey Kurakin Ian Goodfellow Jascha Narain Sohl-Dickstein AAML 117 264 0 22 Feb 2018
Asynchronous Byzantine Machine Learning (the case of SGD) Georgios Damaskinos El-Mahdi El-Mhamdi R. Guerraoui Rhicheek Patra Mahsa Taziki FedML 79 42 0 22 Feb 2018
Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning Christopher Frederickson Michael Moore Glenn Dawson R. Polikar AAML 62 33 0 20 Feb 2018
Out-distribution training confers robustness to deep neural networks Mahdieh Abbasi Christian Gagné OOD 59 1 0 20 Feb 2018
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks J. Uesato Brendan O'Donoghue Aaron van den Oord Pushmeet Kohli AAML 192 606 0 15 Feb 2018
Predicting Adversarial Examples with High Confidence A. Galloway Graham W. Taylor M. Moussa AAML 56 9 0 13 Feb 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks Yusuke Tsuzuku Issei Sato Masashi Sugiyama AAML 117 309 0 12 Feb 2018
VISER: Visual Self-Regularization Hamid Izadinia Pierre Garrigues SSL 75 4 0 07 Feb 2018