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Explaining and Harnessing Adversarial Examples

20 December 2014

Papers citing "Explaining and Harnessing Adversarial Examples"

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Title
Improving Generalization of Deep Neural Networks by Leveraging Margin Distribution Shen-Huan Lyu Lu Wang Zhi Zhou 43 11 0 27 Dec 2018
Adversarial Attack and Defense on Graph Data: A Survey Lichao Sun Yingtong Dou Carl Yang Ji Wang Yixin Liu Philip S. Yu Lifang He Yangqiu Song GNN AAML 139 286 0 26 Dec 2018
A Survey of Deep Facial Attribute Analysis Xin Zheng Yanqing Guo Huaibo Huang Yi Li Ran He CVBM 73 25 0 26 Dec 2018
Seeing isn't Believing: Practical Adversarial Attack Against Object Detectors Yue Zhao Hong Zhu Ruigang Liang Qintao Shen Shengzhi Zhang Kai Chen AAML 65 15 0 26 Dec 2018
A Multiversion Programming Inspired Approach to Detecting Audio Adversarial Examples Qiang Zeng Jianhai Su Chenglong Fu Golam Kayas Lannan Luo AAML 55 46 0 26 Dec 2018
Noise Flooding for Detecting Audio Adversarial Examples Against Automatic Speech Recognition K. Rajaratnam Jugal Kalita AAML 53 44 0 25 Dec 2018
Guessing Smart: Biased Sampling for Efficient Black-Box Adversarial Attacks T. Brunner Frederik Diehl Michael Truong-Le Alois Knoll MLAU AAML 77 117 0 24 Dec 2018
Increasing the adversarial robustness and explainability of capsule networks with $γ$ -capsules David Peer Sebastian Stabinger A. Rodríguez-Sánchez AAML GAN MedIm 54 11 0 23 Dec 2018
Towards resilient machine learning for ransomware detection Li-Wei Chen Chih-Yuan Yang Anindya Paul R. Sahita AAML 36 22 0 21 Dec 2018
Analysis Methods in Neural Language Processing: A Survey Yonatan Belinkov James R. Glass 125 558 0 21 Dec 2018
Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and AICS'2019 Challenge Deqiang Li Qianmu Li Yanfang Ye Shouhuai Xu AAML 64 15 0 19 Dec 2018
Deep Transfer Learning for Static Malware Classification Li-Wei Chen 64 47 0 18 Dec 2018
PROVEN: Certifying Robustness of Neural Networks with a Probabilistic Approach Tsui-Wei Weng Pin-Yu Chen Lam M. Nguyen M. Squillante Ivan Oseledets Luca Daniel AAML 85 30 0 18 Dec 2018
A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability Xiaowei Huang Daniel Kroening Wenjie Ruan Marta Kwiatkowska Youcheng Sun Emese Thamo Min Wu Xinping Yi AAML 132 51 0 18 Dec 2018
Spartan Networks: Self-Feature-Squeezing Neural Networks for increased robustness in adversarial settings François Menet Paul Berthier José M. Fernandez M. Gagnon AAML 27 10 0 17 Dec 2018
Defense-VAE: A Fast and Accurate Defense against Adversarial Attacks Xiang Li Shihao Ji AAML 75 26 0 17 Dec 2018
Perturbation Analysis of Learning Algorithms: A Unifying Perspective on Generation of Adversarial Examples E. Balda Arash Behboodi R. Mathar AAML 32 5 0 15 Dec 2018
Adversarial Sample Detection for Deep Neural Network through Model Mutation Testing Jingyi Wang Guoliang Dong Jun Sun Xinyu Wang Peixin Zhang AAML 80 191 0 14 Dec 2018
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem Matthias Hein Maksym Andriushchenko Julian Bitterwolf OODD 214 559 0 13 Dec 2018
TextBugger: Generating Adversarial Text Against Real-world Applications Jinfeng Li S. Ji Tianyu Du Bo Li Ting Wang SILM AAML 225 750 0 13 Dec 2018
Thwarting Adversarial Examples: An $L_0$ -RobustSparse Fourier Transform Mitali Bafna Jack Murtagh Nikhil Vyas AAML 69 48 0 12 Dec 2018
Deep Anomaly Detection with Outlier Exposure Dan Hendrycks Mantas Mazeika Thomas G. Dietterich OODD 197 1,491 0 11 Dec 2018
Classification-Reconstruction Learning for Open-Set Recognition Ryota Yoshihashi Wen Shao Rei Kawakami Shaodi You M. Iida T. Naemura BDL 86 329 0 11 Dec 2018
Defending Against Universal Perturbations With Shared Adversarial Training Chaithanya Kumar Mummadi Thomas Brox J. H. Metzen AAML 84 60 0 10 Dec 2018
Learning Transferable Adversarial Examples via Ghost Networks Yingwei Li S. Bai Yuyin Zhou Cihang Xie Zhishuai Zhang Alan Yuille AAML 132 137 0 09 Dec 2018
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu Laurens van der Maaten Alan Yuille Kaiming He 177 916 0 09 Dec 2018
AutoGAN: Robust Classifier Against Adversarial Attacks Blerta Lindqvist Shridatt Sugrim R. Izmailov AAML 38 7 0 08 Dec 2018
Combatting Adversarial Attacks through Denoising and Dimensionality Reduction: A Cascaded Autoencoder Approach R. Sahay Rehana Mahfuz Aly El Gamal 55 34 0 07 Dec 2018
Adversarial Defense of Image Classification Using a Variational Auto-Encoder Yi-Si Luo H. Pfister AAML 51 9 0 07 Dec 2018
A Survey of Unsupervised Deep Domain Adaptation Garrett Wilson D. Cook OOD 209 824 0 06 Dec 2018
Fooling Network Interpretation in Image Classification Akshayvarun Subramanya Vipin Pillai Hamed Pirsiavash AAML FAtt 49 7 0 06 Dec 2018
The Limitations of Model Uncertainty in Adversarial Settings Kathrin Grosse David Pfaff M. Smith Michael Backes AAML 63 34 0 06 Dec 2018
Prior Networks for Detection of Adversarial Attacks A. Malinin Mark Gales AAML 69 5 0 06 Dec 2018
Towards Leveraging the Information of Gradients in Optimization-based Adversarial Attack Jingyang Zhang Hsin-Pai Cheng Chunpeng Wu Hai Helen Li Yiran Chen AAML 41 0 0 06 Dec 2018
Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples Huangyi Ge Sze Yiu Chau Bruno Ribeiro Ninghui Li AAML 41 1 0 05 Dec 2018
Rigorous Agent Evaluation: An Adversarial Approach to Uncover Catastrophic Failures Junhui Yin Jiayan Qiu Csaba Szepesvári Siqing Zhang Avraham Ruderman Jiyang Xie Krishnamurthy Dvijotham Zhanyu Ma N. Heess Pushmeet Kohli AAML 107 82 0 04 Dec 2018
Parameter Re-Initialization through Cyclical Batch Size Schedules Norman Mu Z. Yao A. Gholami Kurt Keutzer Michael W. Mahoney ODL 70 8 0 04 Dec 2018
Adversarial Example Decomposition Horace He Aaron Lou Qingxuan Jiang Isay Katsman Serge J. Belongie Ser-Nam Lim AAML 28 0 0 04 Dec 2018
Interpretable Deep Learning under Fire Xinyang Zhang Ningfei Wang Hua Shen S. Ji Xiapu Luo Ting Wang AAML AI4CE 138 174 0 03 Dec 2018
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 313 285 0 03 Dec 2018
Universal Perturbation Attack Against Image Retrieval Jie Li Rongrong Ji Hong Liu Xiaopeng Hong Yue Gao Q. Tian AAML 98 100 0 03 Dec 2018
Model-Reuse Attacks on Deep Learning Systems Yujie Ji Xinyang Zhang S. Ji Xiapu Luo Ting Wang SILM AAML 219 187 0 02 Dec 2018
Probabilistic Verification of Fairness Properties via Concentration Osbert Bastani Xin Zhang Armando Solar-Lezama FaML FedML 88 72 0 02 Dec 2018
SentiNet: Detecting Localized Universal Attacks Against Deep Learning Systems Edward Chou Florian Tramèr Giancarlo Pellegrino AAML 240 295 0 02 Dec 2018
Effects of Loss Functions And Target Representations on Adversarial Robustness Sean Saito S. Roy AAML 72 7 0 01 Dec 2018
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification Qi Lei Lingfei Wu Pin-Yu Chen A. Dimakis Inderjit S. Dhillon Michael Witbrock AAML 102 92 0 01 Dec 2018
Adversarial Defense by Stratified Convolutional Sparse Coding Bo Sun Nian-hsuan Tsai Fangchen Liu Ronald Yu Hao Su AAML 83 76 0 30 Nov 2018
ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples Xiaojun Jia Xingxing Wei Xiaochun Cao H. Foroosh AAML 147 271 0 30 Nov 2018
Transferable Adversarial Attacks for Image and Video Object Detection Xingxing Wei Siyuan Liang Ning Chen Xiaochun Cao AAML 142 225 0 30 Nov 2018
3D Semi-Supervised Learning with Uncertainty-Aware Multi-View Co-Training Yingda Xia Fengze Liu Ke Wang Jinzheng Cai Lequan Yu Zhuotun Zhu Daguang Xu Alan Yuille H. Roth 246 128 0 29 Nov 2018