Parseval Networks: Improving Robustness to Adversarial Examples

28 April 2017

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

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Title
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip H. S. Torr NoLa AAML 23 57 0 08 Jul 2020
Fast Training of Deep Neural Networks Robust to Adversarial Perturbations Justin A. Goodwin Olivia M. Brown Victoria Helus OOD AAML 12 3 0 08 Jul 2020
Robust Learning with Frequency Domain Regularization Weiyu Guo Yidong Ouyang AAML 6 2 0 07 Jul 2020
On Connections between Regularizations for Improving DNN Robustness Yiwen Guo Long Chen Yurong Chen Changshui Zhang AAML 11 14 0 04 Jul 2020
Efficient Proximal Mapping of the 1-path-norm of Shallow Networks Fabian Latorre Paul Rolland Nadav Hallak V. Cevher AAML 13 4 0 02 Jul 2020
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey S. Silva Peyman Najafirad AAML OOD 23 131 0 01 Jul 2020
Deep Isometric Learning for Visual Recognition Haozhi Qi Chong You X. Wang Yi-An Ma Jitendra Malik VLM 24 53 0 30 Jun 2020
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning Lionel Blondé Pablo Strasser Alexandros Kalousis 25 22 0 28 Jun 2020
A general framework for defining and optimizing robustness Alessandro Tibo M. Jaeger Kim G. Larsen 10 0 0 19 Jun 2020
Model-Aware Regularization For Learning Approaches To Inverse Problems Jaweria Amjad Zhaoyang Lyu M. Rodrigues MedIm 6 0 0 18 Jun 2020
Globally Injective ReLU Networks Michael Puthawala K. Kothari Matti Lassas Ivan Dokmanić Maarten V. de Hoop 13 26 0 15 Jun 2020
On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory Alexandre Araujo Benjamin Négrevergne Y. Chevaleyre Jamal Atif 18 0 0 15 Jun 2020
On Saliency Maps and Adversarial Robustness Puneet Mangla Vedant Singh V. Balasubramanian AAML 8 16 0 14 Jun 2020
Rethinking Clustering for Robustness Motasem Alfarra Juan C. Pérez Adel Bibi Ali K. Thabet Pablo Arbelaez Bernard Ghanem OOD 19 0 0 13 Jun 2020
Achieving robustness in classification using optimal transport with hinge regularization M. Serrurier Franck Mamalet Alberto González Sanz Thibaut Boissin Jean-Michel Loubes E. del Barrio AAML 12 39 0 11 Jun 2020
Towards an Intrinsic Definition of Robustness for a Classifier Théo Giraudon Vincent Gripon Matthias Löwe Franck Vermet OOD AAML 9 2 0 09 Jun 2020
The Lipschitz Constant of Self-Attention Hyunjik Kim George Papamakarios A. Mnih 14 134 0 08 Jun 2020
All your loss are belong to Bayes Christian J. Walder Richard Nock 6 5 0 08 Jun 2020
Distributional Robustness with IPMs and links to Regularization and GANs Hisham Husain 14 21 0 08 Jun 2020
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods Kyungmi Lee A. Chandrakasan ELM AAML 6 3 0 01 Jun 2020
Quantized Neural Networks: Characterization and Holistic Optimization Yoonho Boo Sungho Shin Wonyong Sung MQ 40 8 0 31 May 2020
Exploring Model Robustness with Adaptive Networks and Improved Adversarial Training Zheng Xu Ali Shafahi Tom Goldstein AAML 19 2 0 30 May 2020
Calibrated Surrogate Losses for Adversarially Robust Classification Han Bao Clayton Scott Masashi Sugiyama 14 45 0 28 May 2020
Model-Based Robust Deep Learning: Generalizing to Natural, Out-of-Distribution Data Alexander Robey Hamed Hassani George J. Pappas OOD 35 42 0 20 May 2020
Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce Juntao Li Chang Liu Jian Wang Lidong Bing Hongsong Li Xiaozhong Liu Dongyan Zhao Rui Yan 12 12 0 17 May 2020
Lifted Regression/Reconstruction Networks R. Høier Christopher Zach 6 7 0 07 May 2020
Training robust neural networks using Lipschitz bounds Patricia Pauli Anne Koch J. Berberich Paul Kohler Frank Allgöwer 19 156 0 06 May 2020
CWY Parametrization: a Solution for Parallelized Optimization of Orthogonal and Stiefel Matrices Valerii Likhosherstov Jared Davis K. Choromanski Adrian Weller 20 4 0 18 Apr 2020
On Adversarial Examples and Stealth Attacks in Artificial Intelligence Systems I. Tyukin D. Higham A. Gorban AAML 6 39 0 09 Apr 2020
Controllable Orthogonalization in Training DNNs Lei Huang Li Liu Fan Zhu Diwen Wan Zehuan Yuan Bo Li Ling Shao 14 42 0 02 Apr 2020
Dataless Model Selection with the Deep Frame Potential Calvin Murdock Simon Lucey 33 6 0 30 Mar 2020
What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective Qilong Wang Li Zhang Banggu Wu Dongwei Ren P. Li W. Zuo Q. Hu 6 21 0 25 Mar 2020
Defense Through Diverse Directions Christopher M. Bender Yang Li Yifeng Shi Michael K. Reiter Junier B. Oliva AAML 6 4 0 24 Mar 2020
Double Backpropagation for Training Autoencoders against Adversarial Attack Chengjin Sun Sizhe Chen Xiaolin Huang SILM AAML 18 5 0 04 Mar 2020
Exactly Computing the Local Lipschitz Constant of ReLU Networks Matt Jordan A. Dimakis 6 112 0 02 Mar 2020
Improving Robustness of Deep-Learning-Based Image Reconstruction Ankit Raj Y. Bresler Bo-wen Li OOD AAML 17 50 0 26 Feb 2020
Attacks Which Do Not Kill Training Make Adversarial Learning Stronger Jingfeng Zhang Xilie Xu Bo Han Gang Niu Li-zhen Cui Masashi Sugiyama Mohan S. Kankanhalli AAML 22 396 0 26 Feb 2020
$Gradient $\ell_1$ Regularization for Quantization Robustness$ Gradient $\ell_1$ Regularization for Quantization Robustness Milad Alizadeh Arash Behboodi M. V. Baalen Christos Louizos Tijmen Blankevoort Max Welling MQ 12 8 0 18 Feb 2020
Deflecting Adversarial Attacks Yao Qin Nicholas Frosst Colin Raffel G. Cottrell Geoffrey E. Hinton AAML 20 15 0 18 Feb 2020
ResiliNet: Failure-Resilient Inference in Distributed Neural Networks Ashkan Yousefpour Brian Q. Nguyen Siddartha Devic Guanhua Wang Aboudy Kreidieh Hans Lobel Alexandre M. Bayen J. Jue 10 2 0 18 Feb 2020
Regularized Training and Tight Certification for Randomized Smoothed Classifier with Provable Robustness Huijie Feng Chunpeng Wu Guoyang Chen Weifeng Zhang Y. Ning AAML 23 11 0 17 Feb 2020
Generalised Lipschitz Regularisation Equals Distributional Robustness Zac Cranko Zhan Shi Xinhua Zhang Richard Nock Simon Kornblith OOD 10 20 0 11 Feb 2020
Understanding the Decision Boundary of Deep Neural Networks: An Empirical Study David Mickisch F. Assion Florens Greßner W. Günther M. Motta AAML 19 34 0 05 Feb 2020
Efficient Riemannian Optimization on the Stiefel Manifold via the Cayley Transform Jun Li Fuxin Li S. Todorovic 14 99 0 04 Feb 2020
REST: Robust and Efficient Neural Networks for Sleep Monitoring in the Wild Rahul Duggal Scott Freitas Cao Xiao Duen Horng Chau Jimeng Sun 25 22 0 29 Jan 2020
PaRoT: A Practical Framework for Robust Deep Neural Network Training Edward W. Ayers Francisco Eiras Majd Hawasly I. Whiteside OOD 23 19 0 07 Jan 2020
ATHENA: A Framework based on Diverse Weak Defenses for Building Adversarial Defense Meng Jianhai Su Jason M. O'Kane Pooyan Jamshidi AAML 9 7 0 02 Jan 2020
Benchmarking Adversarial Robustness Yinpeng Dong Qi-An Fu Xiao Yang Tianyu Pang Hang Su Zihao Xiao Jun Zhu AAML 23 36 0 26 Dec 2019
Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized Smoothing Jinyuan Jia Xiaoyu Cao Binghui Wang Neil Zhenqiang Gong AAML 24 92 0 20 Dec 2019
Asynchronous Federated Learning with Differential Privacy for Edge Intelligence Yanan Li Shusen Yang Xuebin Ren Cong Zhao FedML 16 33 0 17 Dec 2019