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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
Adversarial Robustness Curves Christina Göpfert Jan Philip Göpfert Barbara Hammer AAML 35 6 0 31 Jul 2019
Adversarial Test on Learnable Image Encryption Maungmaung Aprilpyone Warit Sirichotedumrong Hitoshi Kiya 42 8 0 31 Jul 2019
Not All Adversarial Examples Require a Complex Defense: Identifying Over-optimized Adversarial Examples with IQR-based Logit Thresholding Utku Ozbulak Arnout Van Messem W. D. Neve AAML 34 1 0 30 Jul 2019
Are Odds Really Odd? Bypassing Statistical Detection of Adversarial Examples Hossein Hosseini Sreeram Kannan Radha Poovendran AAML 70 19 0 28 Jul 2019
Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment Di Jin Zhijing Jin Qiufeng Wang Peter Szolovits SILM AAML 321 1,098 0 27 Jul 2019
Defense Against Adversarial Attacks Using Feature Scattering-based Adversarial Training Haichao Zhang Jianyu Wang AAML 112 231 0 24 Jul 2019
Joint Adversarial Training: Incorporating both Spatial and Pixel Attacks Haichao Zhang Jianyu Wang 72 4 0 24 Jul 2019
Towards Adversarially Robust Object Detection Haichao Zhang Jianyu Wang AAML ObjD 139 131 0 24 Jul 2019
Understanding Adversarial Robustness Through Loss Landscape Geometries Vinay Uday Prabhu Dian Ang Yap Joyce Xu John Whaley AAML 58 17 0 22 Jul 2019
Adversarial Security Attacks and Perturbations on Machine Learning and Deep Learning Methods Arif Siddiqi AAML 64 11 0 17 Jul 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt Basel Alomair OODD 318 1,487 0 16 Jul 2019
Latent Adversarial Defence with Boundary-guided Generation Xiaowei Zhou Ivor W. Tsang Jie Yin AAML 47 4 0 16 Jul 2019
Graph Interpolating Activation Improves Both Natural and Robust Accuracies in Data-Efficient Deep Learning Bao Wang Stanley J. Osher AAML AI4CE 77 10 0 16 Jul 2019
Unsupervised Adversarial Attacks on Deep Feature-based Retrieval with GAN Guoping Zhao Mingyu Zhang Jiajun Liu Ji-Rong Wen AAML GAN 65 25 0 12 Jul 2019
Why Blocking Targeted Adversarial Perturbations Impairs the Ability to Learn Ziv Katzir Yuval Elovici AAML 20 3 0 11 Jul 2019
PhysGAN: Generating Physical-World-Resilient Adversarial Examples for Autonomous Driving Zelun Kong Junfeng Guo Ang Li Cong Liu AAML 105 131 0 09 Jul 2019
Adversarial Robustness through Local Linearization Chongli Qin James Martens Sven Gowal Dilip Krishnan Krishnamurthy Dvijotham Alhussein Fawzi Soham De Robert Stanforth Pushmeet Kohli AAML 129 308 0 04 Jul 2019
Fooling a Real Car with Adversarial Traffic Signs N. Morgulis Alexander Kreines Shachar Mendelowitz Yuval Weisglass AAML 89 93 0 30 Jun 2019
Signed Laplacian Deep Learning with Adversarial Augmentation for Improved Mammography Diagnosis Heyi Li Dongdong Chen W. Nailon Mike E. Davies Dave Laurenson MedIm 150 15 0 30 Jun 2019
Training individually fair ML models with Sensitive Subspace Robustness Mikhail Yurochkin Amanda Bower Yuekai Sun FaML OOD 88 120 0 28 Jun 2019
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty Dan Hendrycks Mantas Mazeika Saurav Kadavath Basel Alomair OOD SSL 90 955 0 28 Jun 2019
Learning to Cope with Adversarial Attacks Xian Yeow Lee Aaron J. Havens Girish Chowdhary Soumik Sarkar AAML 73 5 0 28 Jun 2019
Using Intuition from Empirical Properties to Simplify Adversarial Training Defense Guanxiong Liu Issa M. Khalil Abdallah Khreishah AAML 37 2 0 27 Jun 2019
Adversarial Robustness via Label-Smoothing Morgane Goibert Elvis Dohmatob AAML 124 18 0 27 Jun 2019
Defending Adversarial Attacks by Correcting logits Yifeng Li Lingxi Xie Ya Zhang Rui Zhang Yanfeng Wang Qi Tian AAML 44 5 0 26 Jun 2019
Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization Xuhua Ren Lichi Zhang Qian Wang Dinggang Shen 29 12 0 25 Jun 2019
A Game-Theoretic Approach to Adversarial Linear Support Vector Classification Farhad Farokhi AAML 52 3 0 24 Jun 2019
On Physical Adversarial Patches for Object Detection Mark Lee Zico Kolter AAML 95 171 0 20 Jun 2019
Global Adversarial Attacks for Assessing Deep Learning Robustness Hanbin Hu Mitt Shah Jianhua Z. Huang Peng Li AAML 80 4 0 19 Jun 2019
Convergence of Adversarial Training in Overparametrized Neural Networks Ruiqi Gao Tianle Cai Haochuan Li Liwei Wang Cho-Jui Hsieh Jason D. Lee AAML 117 109 0 19 Jun 2019
The Attack Generator: A Systematic Approach Towards Constructing Adversarial Attacks F. Assion Peter Schlicht Florens Greßner W. Günther Fabian Hüger Nico M. Schmidt Umair Rasheed AAML 75 14 0 17 Jun 2019
Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Too Much Accuracy Alex Lamb Vikas Verma Kenji Kawaguchi Alexander Matyasko Savya Khosla Arno Solin Yoshua Bengio AAML 74 100 0 16 Jun 2019
Towards Stable and Efficient Training of Verifiably Robust Neural Networks Huan Zhang Hongge Chen Chaowei Xiao Sven Gowal Robert Stanforth Yue Liu Duane S. Boning Cho-Jui Hsieh AAML 109 351 0 14 Jun 2019
Efficient and Accurate Estimation of Lipschitz Constants for Deep Neural Networks Mahyar Fazlyab Alexander Robey Hamed Hassani M. Morari George J. Pappas 186 462 0 12 Jun 2019
Subspace Attack: Exploiting Promising Subspaces for Query-Efficient Black-box Attacks Ziang Yan Yiwen Guo Changshui Zhang AAML 81 111 0 11 Jun 2019
Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective Kaidi Xu Hongge Chen Sijia Liu Pin-Yu Chen Tsui-Wei Weng Mingyi Hong Xue Lin AAML 131 454 0 10 Jun 2019
Robustness Verification of Tree-based Models Hongge Chen Huan Zhang Si Si Yang Li Duane S. Boning Cho-Jui Hsieh AAML 103 77 0 10 Jun 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman Greg Yang Jungshian Li Pengchuan Zhang Huan Zhang Ilya P. Razenshteyn Sébastien Bubeck AAML 152 552 0 09 Jun 2019
Federated AI lets a team imagine together: Federated Learning of GANs R. A N. V FedML 58 6 0 09 Jun 2019
ML-LOO: Detecting Adversarial Examples with Feature Attribution Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Michael I. Jordan AAML 93 101 0 08 Jun 2019
Strategies to architect AI Safety: Defense to guard AI from Adversaries R. A N. V AAML 32 0 0 08 Jun 2019
Efficient Project Gradient Descent for Ensemble Adversarial Attack Fanyou Wu R. Gazo E. Haviarova Bedrich Benes AAML 33 5 0 07 Jun 2019
Understanding Adversarial Behavior of DNNs by Disentangling Non-Robust and Robust Components in Performance Metric Yujun Shi B. Liao Guangyong Chen Yun-Hai Liu Ming-Ming Cheng Jiashi Feng AAML 20 2 0 06 Jun 2019
Adversarial Risk Bounds for Neural Networks through Sparsity based Compression E. Balda Arash Behboodi Niklas Koep R. Mathar AAML 82 8 0 03 Jun 2019
Fast and Stable Interval Bounds Propagation for Training Verifiably Robust Models P. Morawiecki Przemysław Spurek Marek Śmieja Jacek Tabor AAML OOD 29 9 0 03 Jun 2019
Adversarial Examples for Edge Detection: They Exist, and They Transfer Christian Cosgrove Alan Yuille AAML GAN 51 12 0 02 Jun 2019
Enhancing Transformation-based Defenses using a Distribution Classifier C. Kou H. Lee E. Chang Teck Khim Ng 69 3 0 01 Jun 2019
Are Labels Required for Improving Adversarial Robustness? J. Uesato Jean-Baptiste Alayrac Po-Sen Huang Robert Stanforth Alhussein Fawzi Pushmeet Kohli AAML 97 335 0 31 May 2019
Bandlimiting Neural Networks Against Adversarial Attacks Yuping Lin A. KasraAhmadiK. Hui Jiang AAML 42 6 0 30 May 2019
Controlling Neural Level Sets Matan Atzmon Niv Haim Lior Yariv Ofer Israelov Haggai Maron Y. Lipman AI4CE 54 121 0 28 May 2019