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Parseval Networks: Improving Robustness to Adversarial Examples

28 April 2017

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

50 / 489 papers shown

Title
Analyzing the Noise Robustness of Deep Neural Networks Mengchen Liu Shixia Liu Hang Su Kelei Cao Jun Zhu AAML 70 7 0 09 Oct 2018
Information Geometry of Orthogonal Initializations and Training Piotr A. Sokól Il-Su Park AI4CE 136 17 0 09 Oct 2018
Adversarial Examples - A Complete Characterisation of the Phenomenon A. Serban E. Poll Joost Visser SILM AAML 102 49 0 02 Oct 2018
Improving Sentence Representations with Consensus Maximisation Shuai Tang V. D. Sa SSL AI4TS 51 4 0 02 Oct 2018
Improved robustness to adversarial examples using Lipschitz regularization of the loss Chris Finlay Adam M. Oberman B. Abbasi 80 34 0 01 Oct 2018
A Kernel Perspective for Regularizing Deep Neural Networks A. Bietti Grégoire Mialon Dexiong Chen Julien Mairal 82 15 0 30 Sep 2018
Interpreting Adversarial Robustness: A View from Decision Surface in Input Space Fuxun Yu Chenchen Liu Yanzhi Wang Liang Zhao Xiang Chen AAML OOD 92 27 0 29 Sep 2018
HashTran-DNN: A Framework for Enhancing Robustness of Deep Neural Networks against Adversarial Malware Samples Deqiang Li Ramesh Baral Tao Li Han Wang Qianmu Li Shouhuai Xu AAML 63 21 0 18 Sep 2018
Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization Edoardo Ponti Ivan Vulić Goran Glavaš N. Mrksic Anna Korhonen VLM 63 48 0 11 Sep 2018
Structure-Preserving Transformation: Generating Diverse and Transferable Adversarial Examples Dan Peng Zizhan Zheng Xiaofeng Zhang AAML 57 5 0 08 Sep 2018
Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning Shuai Tang V. D. Sa SSL 51 1 0 08 Sep 2018
Lipschitz Networks and Distributional Robustness Zac Cranko Simon Kornblith Zhan Shi Richard Nock OOD 63 11 0 04 Sep 2018
Lipschitz regularized Deep Neural Networks generalize and are adversarially robust Chris Finlay Jeff Calder Bilal Abbasi Adam M. Oberman 95 55 0 28 Aug 2018
Unsupervised Multilingual Word Embeddings Xilun Chen Claire Cardie 70 132 0 27 Aug 2018
Adversarial Attacks Against Automatic Speech Recognition Systems via Psychoacoustic Hiding Lea Schonherr Katharina Kohls Steffen Zeiler Thorsten Holz D. Kolossa AAML 89 291 0 16 Aug 2018
Is Robustness the Cost of Accuracy? -- A Comprehensive Study on the Robustness of 18 Deep Image Classification Models D. Su Huan Zhang Hongge Chen Jinfeng Yi Pin-Yu Chen Yupeng Gao VLM 140 393 0 05 Aug 2018
Learning Overparameterized Neural Networks via Stochastic Gradient Descent on Structured Data Yuanzhi Li Yingyu Liang MLT 226 653 0 03 Aug 2018
Rob-GAN: Generator, Discriminator, and Adversarial Attacker Xuanqing Liu Cho-Jui Hsieh GAN 66 6 0 27 Jul 2018
Limitations of the Lipschitz constant as a defense against adversarial examples Todd P. Huster C. Chiang R. Chadha AAML 60 84 0 25 Jul 2018
Motivating the Rules of the Game for Adversarial Example Research Justin Gilmer Ryan P. Adams Ian Goodfellow David G. Andersen George E. Dahl AAML 107 229 0 18 Jul 2018
Implicit Generative Modeling of Random Noise during Training for Adversarial Robustness Priyadarshini Panda Kaushik Roy AAML 50 4 0 05 Jul 2018
Efficient ConvNets for Analog Arrays Malte J. Rasch Tayfun Gokmen Mattia Rigotti W. Haensch 57 11 0 03 Jul 2018
Analysis of Invariance and Robustness via Invertibility of ReLU-Networks Jens Behrmann Sören Dittmer Pascal Fernsel Peter Maass 100 12 0 25 Jun 2018
Monge blunts Bayes: Hardness Results for Adversarial Training Zac Cranko A. Menon Richard Nock Cheng Soon Ong Zhan Shi Christian J. Walder AAML 73 17 0 08 Jun 2018
The Nonlinearity Coefficient - Predicting Generalization in Deep Neural Networks George Philipp J. Carbonell 66 14 0 01 Jun 2018
Adversarial Noise Attacks of Deep Learning Architectures -- Stability Analysis via Sparse Modeled Signals Yaniv Romano Aviad Aberdam Jeremias Sulam Michael Elad AAML 73 22 0 29 May 2018
The Singular Values of Convolutional Layers Hanie Sedghi Vineet Gupta Philip M. Long FAtt 93 203 0 26 May 2018
Laplacian Networks: Bounding Indicator Function Smoothness for Neural Network Robustness Carlos Lassance Vincent Gripon Antonio Ortega AAML 88 16 0 24 May 2018
Adversarially Robust Training through Structured Gradient Regularization Kevin Roth Aurelien Lucchi Sebastian Nowozin Thomas Hofmann 72 23 0 22 May 2018
Constructing Unrestricted Adversarial Examples with Generative Models Yang Song Rui Shu Nate Kushman Stefano Ermon GAN AAML 218 307 0 21 May 2018
Detecting Adversarial Samples for Deep Neural Networks through Mutation Testing Jingyi Wang Jun Sun Peixin Zhang Xinyu Wang AAML 76 41 0 14 May 2018
NAIS-Net: Stable Deep Networks from Non-Autonomous Differential Equations Marco Ciccone Marco Gallieri Jonathan Masci Christian Osendorfer Faustino J. Gomez 117 57 0 19 Apr 2018
Regularisation of Neural Networks by Enforcing Lipschitz Continuity Henry Gouk E. Frank Bernhard Pfahringer M. Cree 182 484 0 12 Apr 2018
Deep Neural Networks Motivated by Partial Differential Equations Lars Ruthotto E. Haber AI4CE 161 493 0 12 Apr 2018
Adversarial Training Versus Weight Decay A. Galloway T. Tanay Graham W. Taylor AAML 70 23 0 10 Apr 2018
Defending against Adversarial Images using Basis Functions Transformations Uri Shaham J. Garritano Yutaro Yamada Ethan Weinberger A. Cloninger Xiuyuan Cheng Kelly P. Stanton Y. Kluger AAML 69 57 0 28 Mar 2018
Stabilizing Gradients for Deep Neural Networks via Efficient SVD Parameterization Jiong Zhang Qi Lei Inderjit S. Dhillon 64 112 0 25 Mar 2018
Deep Convolutional Compressed Sensing for LiDAR Depth Completion Nathaniel Chodosh Chaoyang Wang Simon Lucey 3DPC 3DV 71 127 0 23 Mar 2018
Improving DNN Robustness to Adversarial Attacks using Jacobian Regularization Daniel Jakubovitz Raja Giryes AAML 99 210 0 23 Mar 2018
Deep Component Analysis via Alternating Direction Neural Networks Calvin Murdock Ming-Fang Chang Simon Lucey BDL 79 20 0 16 Mar 2018
Large Margin Deep Networks for Classification Gamaleldin F. Elsayed Dilip Krishnan H. Mobahi Kevin Regan Samy Bengio MQ 74 285 0 15 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
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 156 508 0 13 Mar 2018
Adversarial Extreme Multi-label Classification Rohit Babbar Bernhard Schölkopf 60 16 0 05 Mar 2018
Knowledge Transfer with Jacobian Matching Suraj Srinivas François Fleuret 60 171 0 01 Mar 2018
Retrieval-Augmented Convolutional Neural Networks for Improved Robustness against Adversarial Examples Jake Zhao Kyunghyun Cho AAML 160 20 0 26 Feb 2018
Adversarial vulnerability for any classifier Alhussein Fawzi Hamza Fawzi Omar Fawzi AAML 134 251 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
Asynchronous Byzantine Machine Learning (the case of SGD) Georgios Damaskinos El-Mahdi El-Mhamdi R. Guerraoui Rhicheek Patra Mahsa Taziki FedML 79 42 0 22 Feb 2018
The Hidden Vulnerability of Distributed Learning in Byzantium El-Mahdi El-Mhamdi R. Guerraoui Sébastien Rouault AAML FedML 79 769 0 22 Feb 2018