v1v2 (latest)

Parseval Networks: Improving Robustness to Adversarial Examples

28 April 2017

Papers citing "Parseval Networks: Improving Robustness to Adversarial Examples"

39 / 489 papers shown

Title
L2-Nonexpansive Neural Networks Haifeng Qian M. Wegman 75 74 0 22 Feb 2018
i-RevNet: Deep Invertible Networks J. Jacobsen A. Smeulders Edouard Oyallon 85 334 0 20 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
Predicting Adversarial Examples with High Confidence A. Galloway Graham W. Taylor M. Moussa AAML 56 9 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 131 940 0 09 Feb 2018
Fibres of Failure: Classifying errors in predictive processes L. Carlsson Gunnar Carlsson Mikael Vejdemo-Johansson AI4CE 107 4 0 09 Feb 2018
First-order Adversarial Vulnerability of Neural Networks and Input Dimension Carl-Johann Simon-Gabriel Yann Ollivier Léon Bottou Bernhard Schölkopf David Lopez-Paz AAML 111 48 0 05 Feb 2018
Certified Defenses against Adversarial Examples Aditi Raghunathan Jacob Steinhardt Percy Liang AAML 130 969 0 29 Jan 2018
Fooling End-to-end Speaker Verification by Adversarial Examples Felix Kreuk Yossi Adi Moustapha Cissé Joseph Keshet AAML 86 203 0 10 Jan 2018
Adversarial Spheres Justin Gilmer Luke Metz Fartash Faghri S. Schoenholz M. Raghu Martin Wattenberg Ian Goodfellow AAML 74 7 0 09 Jan 2018
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey Naveed Akhtar Ajmal Mian AAML 146 1,873 0 02 Jan 2018
The Robust Manifold Defense: Adversarial Training using Generative Models A. Jalal Andrew Ilyas C. Daskalakis A. Dimakis AAML 109 174 0 26 Dec 2017
Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems Kexin Pei Linjie Zhu Yinzhi Cao Junfeng Yang Carl Vondrick Suman Jana AAML 111 103 0 05 Dec 2017
Improving Network Robustness against Adversarial Attacks with Compact Convolution Rajeev Ranjan S. Sankaranarayanan Carlos D. Castillo Rama Chellappa AAML 65 14 0 03 Dec 2017
Measuring the tendency of CNNs to Learn Surface Statistical Regularities Jason Jo Yoshua Bengio AAML 89 250 0 30 Nov 2017
ConvNets and ImageNet Beyond Accuracy: Understanding Mistakes and Uncovering Biases Pierre Stock Moustapha Cissé FaML 94 46 0 30 Nov 2017
On the Robustness of Semantic Segmentation Models to Adversarial Attacks Anurag Arnab O. Mikšík Philip Torr AAML 115 308 0 27 Nov 2017
Intriguing Properties of Adversarial Examples E. D. Cubuk Barret Zoph S. Schoenholz Quoc V. Le AAML 86 85 0 08 Nov 2017
Provable defenses against adversarial examples via the convex outer adversarial polytope Eric Wong J. Zico Kolter AAML 207 1,506 0 02 Nov 2017
Countering Adversarial Images using Input Transformations Chuan Guo Mayank Rana Moustapha Cissé Laurens van der Maaten AAML 151 1,409 0 31 Oct 2017
PixelDefend: Leveraging Generative Models to Understand and Defend against Adversarial Examples Yang Song Taesup Kim Sebastian Nowozin Stefano Ermon Nate Kushman AAML 145 791 0 30 Oct 2017
Interpretation of Neural Networks is Fragile Amirata Ghorbani Abubakar Abid James Zou FAtt AAML 153 875 0 29 Oct 2017
mixup: Beyond Empirical Risk Minimization Hongyi Zhang Moustapha Cissé Yann N. Dauphin David Lopez-Paz NoLa 323 9,831 0 25 Oct 2017
Word Translation Without Parallel Data Alexis Conneau Guillaume Lample MarcÁurelio Ranzato Ludovic Denoyer Hervé Jégou 309 1,663 0 11 Oct 2017
Orthogonal Weight Normalization: Solution to Optimization over Multiple Dependent Stiefel Manifolds in Deep Neural Networks Lei Huang Xianglong Liu B. Lang Adams Wei Yu Yongliang Wang Bo Li ODL 95 231 0 16 Sep 2017
Art of singular vectors and universal adversarial perturbations Valentin Khrulkov Ivan Oseledets AAML 78 132 0 11 Sep 2017
DeepTest: Automated Testing of Deep-Neural-Network-driven Autonomous Cars Yuchi Tian Kexin Pei Suman Jana Baishakhi Ray AAML 99 1,365 0 28 Aug 2017
Houdini: Fooling Deep Structured Prediction Models Moustapha Cissé Yossi Adi Natalia Neverova Joseph Keshet AAML 96 272 0 17 Jul 2017
Spectrally-normalized margin bounds for neural networks Peter L. Bartlett Dylan J. Foster Matus Telgarsky ODL 345 1,225 0 26 Jun 2017
Group Invariance, Stability to Deformations, and Complexity of Deep Convolutional Representations A. Bietti Julien Mairal 68 8 0 09 Jun 2017
Kronecker Recurrent Units C. Jose Moustapha Cissé François Fleuret ODL 139 46 0 29 May 2017
MAT: A Multi-strength Adversarial Training Method to Mitigate Adversarial Attacks Chang Song Hsin-Pai Cheng Huanrui Yang Sicheng Li Chunpeng Wu Qing Wu H. Li Yiran Chen AAML 59 2 0 27 May 2017
Formal Guarantees on the Robustness of a Classifier against Adversarial Manipulation Matthias Hein Maksym Andriushchenko AAML 131 512 0 23 May 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 217 2,738 0 19 May 2017
DeepXplore: Automated Whitebox Testing of Deep Learning Systems Kexin Pei Yinzhi Cao Junfeng Yang Suman Jana AAML 142 1,376 0 18 May 2017
Optimization on Product Submanifolds of Convolution Kernels Mete Ozay Takayuki Okatani AAML 33 0 0 22 Jan 2017
A Mathematical Theory of Deep Convolutional Neural Networks for Feature Extraction Thomas Wiatowski Helmut Bölcskei FAtt 90 366 0 19 Dec 2015
Understanding Adversarial Training: Increasing Local Stability of Neural Nets through Robust Optimization Uri Shaham Yutaro Yamada S. Negahban AAML 84 78 0 17 Nov 2015