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Towards Evaluating the Robustness of Neural Networks

16 August 2016

Papers citing "Towards Evaluating the Robustness of Neural Networks"

50 / 4,015 papers shown

Title
An ADMM-Based Universal Framework for Adversarial Attacks on Deep Neural Networks Pu Zhao Sijia Liu Yanzhi Wang Xinyu Lin AAML 72 37 0 09 Apr 2018
Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning Matthew Jagielski Alina Oprea Battista Biggio Chang-rui Liu Cristina Nita-Rotaru Yue Liu AAML 104 768 0 01 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
Learning to Anonymize Faces for Privacy Preserving Action Detection Zhongzheng Ren Yong Jae Lee Michael S. Ryoo CVBM PICV 153 205 0 30 Mar 2018
The Effects of JPEG and JPEG2000 Compression on Attacks using Adversarial Examples Ayse Elvan Aydemir A. Temi̇zel T. Taşkaya-Temizel AAML 63 32 0 28 Mar 2018
On the Limitation of Local Intrinsic Dimensionality for Characterizing the Subspaces of Adversarial Examples Pei-Hsuan Lu Pin-Yu Chen Chia-Mu Yu AAML 66 26 0 26 Mar 2018
Clipping free attacks against artificial neural networks B. Addad Jérôme Kodjabachian Christophe Meyer AAML 33 1 0 26 Mar 2018
An Overview of Vulnerabilities of Voice Controlled Systems Yuan Gong C. Poellabauer 51 32 0 24 Mar 2018
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization Daniel Jakubovitz Raja Giryes AAML 99 210 0 23 Mar 2018
Understanding Measures of Uncertainty for Adversarial Example Detection Lewis Smith Y. Gal UQCV 96 365 0 22 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
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems Lei Ma Felix Juefei Xu Fuyuan Zhang Jiyuan Sun Minhui Xue ... Ting Su Li Li Yang Liu Jianjun Zhao Yadong Wang ELM 82 626 0 20 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
Technical Report: When Does Machine Learning FAIL? Generalized Transferability for Evasion and Poisoning Attacks Octavian Suciu R. Marginean Yigitcan Kaya Hal Daumé Tudor Dumitras AAML 88 287 0 19 Mar 2018
A Dual Approach to Scalable Verification of Deep Networks Krishnamurthy Dvijotham Dvijotham Robert Stanforth Sven Gowal Timothy A. Mann Pushmeet Kohli 70 399 0 17 Mar 2018
Semantic Adversarial Examples Hossein Hosseini Radha Poovendran GAN AAML 108 199 0 16 Mar 2018
Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training Derui Wang Chaoran Li S. Wen Surya Nepal Yang Xiang AAML 74 30 0 14 Mar 2018
Feature Distillation: DNN-Oriented JPEG Compression Against Adversarial Examples Zihao Liu Qi Liu Tao Liu Nuo Xu Xue Lin Yanzhi Wang Wujie Wen AAML MQ 92 265 0 14 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
Testing Deep Neural Networks Youcheng Sun Xiaowei Huang Daniel Kroening James Sharp Matthew Hill Rob Ashmore AAML 88 219 0 10 Mar 2018
The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks Jonathan Frankle Michael Carbin 408 3,496 0 09 Mar 2018
Sparse Adversarial Perturbations for Videos Xingxing Wei Jun Zhu Hang Su AAML 81 145 0 07 Mar 2018
Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples Minhao Cheng Jinfeng Yi Pin-Yu Chen Huan Zhang Cho-Jui Hsieh SILM AAML 118 245 0 03 Mar 2018
Protecting JPEG Images Against Adversarial Attacks Aaditya (Adi) Prakash N. Moran Solomon Garber Antonella DiLillo J. Storer AAML 82 34 0 02 Mar 2018
Adversarial Active Learning for Deep Networks: a Margin Based Approach Mélanie Ducoffe F. Precioso GAN AAML 153 278 0 27 Feb 2018
Understanding and Enhancing the Transferability of Adversarial Examples Lei Wu Zhanxing Zhu Cheng Tai E. Weinan AAML SILM 80 99 0 27 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
Verifying Controllers Against Adversarial Examples with Bayesian Optimization Shromona Ghosh Felix Berkenkamp G. Ranade S. Qadeer Ashish Kapoor AAML 103 45 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
Hessian-based Analysis of Large Batch Training and Robustness to Adversaries Z. Yao A. Gholami Qi Lei Kurt Keutzer Michael W. Mahoney 106 167 0 22 Feb 2018
Unravelling Robustness of Deep Learning based Face Recognition Against Adversarial Attacks Gaurav Goswami Nalini Ratha Akshay Agarwal Richa Singh Mayank Vatsa AAML 97 166 0 22 Feb 2018
L2-Nonexpansive Neural Networks Haifeng Qian M. Wegman 75 74 0 22 Feb 2018
Generalizable Adversarial Examples Detection Based on Bi-model Decision Mismatch João Monteiro Isabela Albuquerque Zahid Akhtar T. Falk AAML 90 29 0 21 Feb 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 174 592 0 21 Feb 2018
On Lyapunov exponents and adversarial perturbation Vinay Uday Prabhu Nishant Desai John Whaley AAML 22 4 0 20 Feb 2018
Shield: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression Nilaksh Das Madhuri Shanbhogue Shang-Tse Chen Fred Hohman Siwei Li Li-Wei Chen Michael E. Kounavis Duen Horng Chau FedML AAML 98 228 0 19 Feb 2018
Divide, Denoise, and Defend against Adversarial Attacks Seyed-Mohsen Moosavi-Dezfooli A. Shrivastava Oncel Tuzel AAML 57 45 0 19 Feb 2018
Are Generative Classifiers More Robust to Adversarial Attacks? Yingzhen Li John Bradshaw Yash Sharma AAML 102 79 0 19 Feb 2018
DARTS: Deceiving Autonomous Cars with Toxic Signs Chawin Sitawarin A. Bhagoji Arsalan Mosenia M. Chiang Prateek Mittal AAML 128 236 0 18 Feb 2018
ASP:A Fast Adversarial Attack Example Generation Framework based on Adversarial Saliency Prediction Fuxun Yu Qide Dong Xiang Chen AAML 62 6 0 15 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
Fooling OCR Systems with Adversarial Text Images Congzheng Song Vitaly Shmatikov AAML 65 51 0 15 Feb 2018
Stealing Hyperparameters in Machine Learning Binghui Wang Neil Zhenqiang Gong AAML 178 467 0 14 Feb 2018
Identify Susceptible Locations in Medical Records via Adversarial Attacks on Deep Predictive Models Mengying Sun Fengyi Tang Jinfeng Yi Fei Wang Jiayu Zhou AAML OOD MedIm 85 63 0 13 Feb 2018
Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples Felix Kreuk A. Barak Shir Aviv-Reuven Moran Baruch Benny Pinkas Joseph Keshet AAML 75 118 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
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 176 940 0 09 Feb 2018
TSViz: Demystification of Deep Learning Models for Time-Series Analysis Shoaib Ahmed Siddiqui Dominique Mercier Mohsin Munir Andreas Dengel Sheraz Ahmed FAtt AI4TS 115 84 0 08 Feb 2018