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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
HopSkipJumpAttack: A Query-Efficient Decision-Based Attack Jianbo Chen Michael I. Jordan Martin J. Wainwright AAML 121 672 0 03 Apr 2019
Interpreting Adversarial Examples by Activation Promotion and Suppression Kaidi Xu Sijia Liu Gaoyuan Zhang Mengshu Sun Pu Zhao Quanfu Fan Chuang Gan Xinyu Lin AAML FAtt 147 43 0 03 Apr 2019
Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks Aamir Mustafa Salman Khan Munawar Hayat Roland Göcke Jianbing Shen Ling Shao AAML 64 152 0 01 Apr 2019
Adversarial Robustness vs Model Compression, or Both? Shaokai Ye Kaidi Xu Sijia Liu Jan-Henrik Lambrechts Huan Zhang Aojun Zhou Kaisheng Ma Yanzhi Wang Xue Lin AAML 114 165 0 29 Mar 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 200 3,465 0 28 Mar 2019
IMAE for Noise-Robust Learning: Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude's Variance Matters Xinshao Wang Yang Hua Elyor Kodirov David Clifton N. Robertson NoLa 145 63 0 28 Mar 2019
Defending against Whitebox Adversarial Attacks via Randomized Discretization Yuchen Zhang Percy Liang AAML 84 76 0 25 Mar 2019
Robust Neural Networks using Randomized Adversarial Training Alexandre Araujo Laurent Meunier Rafael Pinot Benjamin Négrevergne AAML OOD 48 36 0 25 Mar 2019
Variational Inference with Latent Space Quantization for Adversarial Resilience Vinay Kyatham P. PrathoshA. Tarun Kumar Yadav Deepak Mishra Dheeraj Mundhra AAML 48 3 0 24 Mar 2019
Scalable Differential Privacy with Certified Robustness in Adversarial Learning Nhathai Phan My T. Thai Han Hu R. Jin Tong Sun Dejing Dou 91 14 0 23 Mar 2019
Improving Adversarial Robustness via Guided Complement Entropy Hao-Yun Chen Jhao-Hong Liang Shih-Chieh Chang Jia Pan Yu-Ting Chen Wei Wei Da-Cheng Juan AAML 67 49 0 23 Mar 2019
Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes Matt Jordan Justin Lewis A. Dimakis AAML 79 57 0 20 Mar 2019
On Certifying Non-uniform Bound against Adversarial Attacks Chen Liu Ryota Tomioka Volkan Cevher AAML 79 19 0 15 Mar 2019
Attribution-driven Causal Analysis for Detection of Adversarial Examples Susmit Jha Sunny Raj S. Fernandes Sumit Kumar Jha S. Jha Gunjan Verma B. Jalaeian A. Swami AAML 75 17 0 14 Mar 2019
GanDef: A GAN based Adversarial Training Defense for Neural Network Classifier Guanxiong Liu Issa M. Khalil Abdallah Khreishah GAN AAML 65 19 0 06 Mar 2019
Defense Against Adversarial Images using Web-Scale Nearest-Neighbor Search Abhimanyu Dubey Laurens van der Maaten Zeki Yalniz Yixuan Li D. Mahajan AAML 115 66 0 05 Mar 2019
A Fundamental Performance Limitation for Adversarial Classification Abed AlRahman Al Makdah Vaibhav Katewa Fabio Pasqualetti AAML 50 9 0 04 Mar 2019
PuVAE: A Variational Autoencoder to Purify Adversarial Examples Uiwon Hwang Jaewoo Park Hyemi Jang Sungroh Yoon N. Cho AAML 75 77 0 02 Mar 2019
Towards Understanding Adversarial Examples Systematically: Exploring Data Size, Task and Model Factors Ke Sun Zhanxing Zhu Zhouchen Lin AAML 76 18 0 28 Feb 2019
The Best Defense Is a Good Offense: Adversarial Attacks to Avoid Modulation Detection Muhammad Zaid Hameed András Gyorgy Deniz Gunduz AAML 83 73 0 27 Feb 2019
Robust Decision Trees Against Adversarial Examples Hongge Chen Huan Zhang Duane S. Boning Cho-Jui Hsieh AAML 142 117 0 27 Feb 2019
Adversarial attacks hidden in plain sight Jan Philip Göpfert André Artelt H. Wersing Barbara Hammer AAML 46 17 0 25 Feb 2019
MaskDGA: A Black-box Evasion Technique Against DGA Classifiers and Adversarial Defenses Lior Sidi Asaf Nadler A. Shabtai AAML 40 22 0 24 Feb 2019
On the Sensitivity of Adversarial Robustness to Input Data Distributions G. Ding Kry Yik-Chau Lui Xiaomeng Jin Luyu Wang Ruitong Huang OOD 64 60 0 22 Feb 2019
Solving a Class of Non-Convex Min-Max Games Using Iterative First Order Methods Maher Nouiehed Maziar Sanjabi Tianjian Huang Jason D. Lee Meisam Razaviyayn 113 344 0 21 Feb 2019
advertorch v0.1: An Adversarial Robustness Toolbox based on PyTorch G. Ding Luyu Wang Xiaomeng Jin 79 183 0 20 Feb 2019
Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure Fuli Feng Xiangnan He Jie Tang Tat-Seng Chua OOD AAML 116 221 0 20 Feb 2019
There are No Bit Parts for Sign Bits in Black-Box Attacks Abdullah Al-Dujaili Una-May O’Reilly AAML 116 20 0 19 Feb 2019
Mockingbird: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces Mohammad Saidur Rahman Mohsen Imani Nate Mathews M. Wright AAML 86 81 0 18 Feb 2019
Model Compression with Adversarial Robustness: A Unified Optimization Framework Shupeng Gui Haotao Wang Chen Yu Haichuan Yang Zhangyang Wang Ji Liu MQ 81 139 0 10 Feb 2019
Discretization based Solutions for Secure Machine Learning against Adversarial Attacks Priyadarshini Panda I. Chakraborty Kaushik Roy AAML 62 40 0 08 Feb 2019
Certified Adversarial Robustness via Randomized Smoothing Jeremy M. Cohen Elan Rosenfeld J. Zico Kolter AAML 247 2,058 0 08 Feb 2019
Robustness Of Saak Transform Against Adversarial Attacks T. Ramanathan Abinaya Manimaran Suya You C.-C. Jay Kuo 76 5 0 07 Feb 2019
Robustness Certificates Against Adversarial Examples for ReLU Networks Sahil Singla Soheil Feizi AAML 68 21 0 01 Feb 2019
A New Family of Neural Networks Provably Resistant to Adversarial Attacks Rakshit Agrawal Luca de Alfaro D. Helmbold AAML OOD 39 2 0 01 Feb 2019
Augmenting Model Robustness with Transformation-Invariant Attacks Houpu Yao Zhe Wang Guangyu Nie Yassine Mazboudi Yezhou Yang Yi Ren AAML OOD 31 3 0 31 Jan 2019
Adversarial Metric Attack and Defense for Person Re-identification S. Bai Yingwei Li Yuyin Zhou Qizhu Li Philip Torr AAML 103 17 0 30 Jan 2019
On the Effect of Low-Rank Weights on Adversarial Robustness of Neural Networks P. Langenberg E. Balda Arash Behboodi R. Mathar 53 16 0 29 Jan 2019
Improving Adversarial Robustness of Ensembles with Diversity Training Sanjay Kariyappa Moinuddin K. Qureshi AAML FedML 88 138 0 28 Jan 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 97 727 0 28 Jan 2019
Value Propagation for Decentralized Networked Deep Multi-agent Reinforcement Learning Chao Qu Shie Mannor Huan Xu Yuan Qi Le Song Junwu Xiong 84 44 0 27 Jan 2019
Improving Adversarial Robustness via Promoting Ensemble Diversity Tianyu Pang Kun Xu Chao Du Ning Chen Jun Zhu AAML 106 441 0 25 Jan 2019
Theoretically Principled Trade-off between Robustness and Accuracy Hongyang R. Zhang Yaodong Yu Jiantao Jiao Eric Xing L. Ghaoui Michael I. Jordan 262 2,566 0 24 Jan 2019
Cross-Entropy Loss and Low-Rank Features Have Responsibility for Adversarial Examples Kamil Nar Orhan Ocal S. Shankar Sastry Kannan Ramchandran AAML 90 54 0 24 Jan 2019
Optimization Problems for Machine Learning: A Survey Claudio Gambella Bissan Ghaddar Joe Naoum-Sawaya AI4CE 145 181 0 16 Jan 2019
The Limitations of Adversarial Training and the Blind-Spot Attack Huan Zhang Hongge Chen Zhao Song Duane S. Boning Inderjit S. Dhillon Cho-Jui Hsieh AAML 76 145 0 15 Jan 2019
Characterizing and evaluating adversarial examples for Offline Handwritten Signature Verification L. G. Hafemann R. Sabourin Luiz Eduardo Soares de Oliveira AAML 55 44 0 10 Jan 2019
Image Transformation can make Neural Networks more robust against Adversarial Examples D. D. Thang Toshihiro Matsui AAML 25 10 0 10 Jan 2019
Extending Adversarial Attacks and Defenses to Deep 3D Point Cloud Classifiers Daniel Liu Ronald Yu Hao Su 3DPC 99 170 0 10 Jan 2019
Image Super-Resolution as a Defense Against Adversarial Attacks Aamir Mustafa Salman H. Khan Munawar Hayat Jianbing Shen Ling Shao AAML SupR 100 176 0 07 Jan 2019