Adversarial Machine Learning at Scale

4 November 2016

Papers citing "Adversarial Machine Learning at Scale"

50 / 1,599 papers shown

Title
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 50 686 0 25 Apr 2018
Towards Dependable Deep Convolutional Neural Networks (CNNs) with Out-distribution Learning Mahdieh Abbasi Arezoo Rajabi Christian Gagné R. Bobba OODD 30 6 0 24 Apr 2018
VectorDefense: Vectorization as a Defense to Adversarial Examples V. Kabilan Brandon L. Morris Anh Totti Nguyen AAML 22 21 0 23 Apr 2018
Decoupled Networks Weiyang Liu Zichen Liu Zhiding Yu Bo Dai Rongmei Lin Yisen Wang James M. Rehg Le Song OOD 19 65 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 258 916 0 21 Apr 2018
ADef: an Iterative Algorithm to Construct Adversarial Deformations Rima Alaifari Giovanni S. Alberti Tandri Gauksson AAML 25 96 0 20 Apr 2018
Learning More Robust Features with Adversarial Training Shuangtao Li Yuanke Chen Yanlin Peng Lin Bai OOD AAML 33 23 0 20 Apr 2018
Robustness via Deep Low-Rank Representations Amartya Sanyal Varun Kanade Philip Torr P. Dokania OOD 27 16 0 19 Apr 2018
Robust Machine Comprehension Models via Adversarial Training Yicheng Wang Joey Tianyi Zhou AAML 36 117 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 57 19 0 14 Apr 2018
Adversarial Training Versus Weight Decay A. Galloway T. Tanay Graham W. Taylor AAML 29 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 34 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 20 318 0 31 Mar 2018
Security Consideration For Deep Learning-Based Image Forensics Wei Zhao Pengpeng Yang R. Ni Yao-Min Zhao Haorui Wu AAML 14 5 0 29 Mar 2018
Bypassing Feature Squeezing by Increasing Adversary Strength Yash Sharma Pin-Yu Chen AAML 19 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 26 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 17 1,100 0 19 Mar 2018
Adversarial Logit Pairing Harini Kannan Alexey Kurakin Ian Goodfellow AAML 36 625 0 16 Mar 2018
Semantic Adversarial Examples Hossein Hosseini Radha Poovendran GAN AAML 40 196 0 16 Mar 2018
Large Margin Deep Networks for Classification Gamaleldin F. Elsayed Dilip Krishnan H. Mobahi Kevin Regan Samy Bengio MQ 22 281 0 15 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 13 504 0 13 Mar 2018
Invisible Mask: Practical Attacks on Face Recognition with Infrared Zhe Zhou Di Tang Xiaofeng Wang Weili Han Xiangyu Liu Kehuan Zhang CVBM AAML 26 103 0 13 Mar 2018
Malytics: A Malware Detection Scheme Mahmood Yousefi-Azar Len Hamey Vijay Varadharajan Shiping Chen 16 40 0 09 Mar 2018
Rethinking Feature Distribution for Loss Functions in Image Classification Weitao Wan Yuanyi Zhong Tianpeng Li Jiansheng Chen 21 166 0 08 Mar 2018
Style Memory: Making a Classifier Network Generative R. Wiyatno Jeff Orchard 20 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 27 54 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 24 138 0 27 Feb 2018
Max-Mahalanobis Linear Discriminant Analysis Networks Tianyu Pang Chao Du Jun Zhu 8 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 24 437 0 23 Feb 2018
Deep Defense: Training DNNs with Improved Adversarial Robustness Ziang Yan Yiwen Guo Changshui Zhang AAML 38 109 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 47 259 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 37 42 0 22 Feb 2018
Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning Christopher Frederickson Michael Moore Glenn Dawson R. Polikar AAML 16 32 0 20 Feb 2018
Out-distribution training confers robustness to deep neural networks Mahdieh Abbasi Christian Gagné OOD 13 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 39 598 0 15 Feb 2018
Predicting Adversarial Examples with High Confidence A. Galloway Graham W. Taylor M. Moussa AAML 29 9 0 13 Feb 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks Yusuke Tsuzuku Issei Sato Masashi Sugiyama AAML 44 298 0 12 Feb 2018
VISER: Visual Self-Regularization Hamid Izadinia Pierre Garrigues SSL 16 4 0 07 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 98 3,160 0 01 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 25 464 0 31 Jan 2018
Generalizable Data-free Objective for Crafting Universal Adversarial Perturbations Konda Reddy Mopuri Aditya Ganeshan R. Venkatesh Babu AAML 40 203 0 24 Jan 2018
Adversarial Deep Learning for Robust Detection of Binary Encoded Malware Abdullah Al-Dujaili Alex Huang Erik Hemberg Una-May O’Reilly AAML 25 186 0 09 Jan 2018
Facial Attributes: Accuracy and Adversarial Robustness Andras Rozsa Manuel Günther Ethan M. Rudd Terrance E. Boult AAML CVBM 24 65 0 04 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey Naveed Akhtar Ajmal Mian AAML 22 1,856 0 02 Jan 2018
A General Framework for Adversarial Examples with Objectives Mahmood Sharif Sruti Bhagavatula Lujo Bauer Michael K. Reiter AAML GAN 13 191 0 31 Dec 2017
Adversarial Examples: Attacks and Defenses for Deep Learning Xiaoyong Yuan Pan He Qile Zhu Xiaolin Li SILM AAML 36 1,612 0 19 Dec 2017
NAG: Network for Adversary Generation Konda Reddy Mopuri Utkarsh Ojha Utsav Garg R. Venkatesh Babu AAML 27 144 0 09 Dec 2017
Defense against Adversarial Attacks Using High-Level Representation Guided Denoiser Fangzhou Liao Ming Liang Yinpeng Dong Tianyu Pang Xiaolin Hu Jun Zhu 33 874 0 08 Dec 2017
Exploring the Landscape of Spatial Robustness Logan Engstrom Brandon Tran Dimitris Tsipras Ludwig Schmidt A. Madry AAML 33 360 0 07 Dec 2017
Generative Adversarial Perturbations Omid Poursaeed Isay Katsman Bicheng Gao Serge J. Belongie AAML GAN WIGM 31 351 0 06 Dec 2017