Adversarially Robust Generalization Requires More Data

30 April 2018

Papers citing "Adversarially Robust Generalization Requires More Data"

50 / 198 papers shown

Title
Adversarial Robustness under Long-Tailed Distribution Tong Wu Ziwei Liu Qingqiu Huang Yu Wang Dahua Lin 26 76 0 06 Apr 2021
Consistency Regularization for Adversarial Robustness Jihoon Tack Sihyun Yu Jongheon Jeong Minseon Kim Sung Ju Hwang Jinwoo Shin AAML 41 57 0 08 Mar 2021
Improving Global Adversarial Robustness Generalization With Adversarially Trained GAN Desheng Wang Wei-dong Jin Yunpu Wu Aamir Khan GAN 36 8 0 08 Mar 2021
Fixing Data Augmentation to Improve Adversarial Robustness Sylvestre-Alvise Rebuffi Sven Gowal D. A. Calian Florian Stimberg Olivia Wiles Timothy A. Mann AAML 36 271 0 02 Mar 2021
A Survey On Universal Adversarial Attack Chaoning Zhang Philipp Benz Chenguo Lin Adil Karjauv Jing Wu In So Kweon AAML 28 90 0 02 Mar 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training Vasu Singla Sahil Singla David Jacobs S. Feizi AAML 43 45 0 15 Feb 2021
Guided Interpolation for Adversarial Training Chen Chen Jingfeng Zhang Xilie Xu Tianlei Hu Gang Niu Gang Chen Masashi Sugiyama AAML 37 10 0 15 Feb 2021
When and How Mixup Improves Calibration Linjun Zhang Zhun Deng Kenji Kawaguchi James Zou UQCV 36 67 0 11 Feb 2021
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao Bihan Wen Qian Wang AAML 86 476 0 02 Feb 2021
Generating Out of Distribution Adversarial Attack using Latent Space Poisoning Ujjwal Upadhyay Prerana Mukherjee 39 7 0 09 Dec 2020
Recent Advances in Understanding Adversarial Robustness of Deep Neural Networks Tao Bai Jinqi Luo Jun Zhao AAML 49 8 0 03 Nov 2020
Adversarial Robust Training of Deep Learning MRI Reconstruction Models Francesco Calivá Kaiyang Cheng Rutwik Shah V. Pedoia OOD AAML MedIm 30 10 0 30 Oct 2020
Robust Pre-Training by Adversarial Contrastive Learning Ziyu Jiang Tianlong Chen Ting-Li Chen Zhangyang Wang 30 228 0 26 Oct 2020
Adversarial Attacks on Binary Image Recognition Systems Eric Balkanski Harrison W. Chase Kojin Oshiba Alexander Rilee Yaron Singer Richard Wang AAML 47 4 0 22 Oct 2020
Precise Statistical Analysis of Classification Accuracies for Adversarial Training Adel Javanmard Mahdi Soltanolkotabi AAML 33 61 0 21 Oct 2020
Optimism in the Face of Adversity: Understanding and Improving Deep Learning through Adversarial Robustness Guillermo Ortiz-Jiménez Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard AAML 39 48 0 19 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 22 325 0 07 Oct 2020
Query complexity of adversarial attacks Grzegorz Gluch R. Urbanke AAML 27 5 0 02 Oct 2020
A law of robustness for two-layers neural networks Sébastien Bubeck Yuanzhi Li Dheeraj M. Nagaraj 35 57 0 30 Sep 2020
Adversarial Robustness of Stabilized NeuralODEs Might be from Obfuscated Gradients Yifei Huang Yaodong Yu Hongyang R. Zhang Yi Ma Yuan Yao AAML 37 26 0 28 Sep 2020
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 31 11 0 21 Sep 2020
Adversarial Machine Learning in Image Classification: A Survey Towards the Defender's Perspective G. R. Machado Eugênio Silva R. Goldschmidt AAML 33 157 0 08 Sep 2020
Addressing Neural Network Robustness with Mixup and Targeted Labeling Adversarial Training Alfred Laugros A. Caplier Matthieu Ospici AAML 24 19 0 19 Aug 2020
A Survey on Large-scale Machine Learning Meng Wang Weijie Fu Xiangnan He Shijie Hao Xindong Wu 25 110 0 10 Aug 2020
Adversarial Examples on Object Recognition: A Comprehensive Survey A. Serban E. Poll Joost Visser AAML 32 73 0 07 Aug 2020
Derivation of Information-Theoretically Optimal Adversarial Attacks with Applications to Robust Machine Learning Jirong Yi R. Mudumbai Weiyu Xu AAML 32 2 0 28 Jul 2020
An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models Lifu Tu Garima Lalwani Spandana Gella He He LRM 33 184 0 14 Jul 2020
Understanding Adversarial Examples from the Mutual Influence of Images and Perturbations Chaoning Zhang Philipp Benz Tooba Imtiaz In-So Kweon SSL AAML 22 118 0 13 Jul 2020
How benign is benign overfitting? Amartya Sanyal P. Dokania Varun Kanade Philip Torr NoLa AAML 25 57 0 08 Jul 2020
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification Chen Dan Yuting Wei Pradeep Ravikumar 26 45 0 29 Jun 2020
Self-training Avoids Using Spurious Features Under Domain Shift Yining Chen Colin Wei Ananya Kumar Tengyu Ma OOD 29 85 0 17 Jun 2020
On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them Chen Liu Mathieu Salzmann Tao R. Lin Ryota Tomioka Sabine Süsstrunk AAML 24 81 0 15 Jun 2020
Provable tradeoffs in adversarially robust classification Yan Sun Hamed Hassani David Hong Alexander Robey 23 53 0 09 Jun 2020
Estimating Principal Components under Adversarial Perturbations Pranjal Awasthi Xue Chen Aravindan Vijayaraghavan AAML 17 2 0 31 May 2020
Arms Race in Adversarial Malware Detection: A Survey Deqiang Li Qianmu Li Yanfang Ye Shouhuai Xu AAML 24 52 0 24 May 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 39 148 0 20 May 2020
PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking Chong Xiang A. Bhagoji Vikash Sehwag Prateek Mittal AAML 30 29 0 17 May 2020
Efficiently Learning Adversarially Robust Halfspaces with Noise Omar Montasser Surbhi Goel Ilias Diakonikolas Nathan Srebro 29 32 0 15 May 2020
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks Pranjal Awasthi Natalie Frank M. Mohri AAML 36 56 0 28 Apr 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 31 8 0 23 Apr 2020
Certifying Joint Adversarial Robustness for Model Ensembles M. Jonas David Evans AAML 21 2 0 21 Apr 2020
Adversarial Robustness: From Self-Supervised Pre-Training to Fine-Tuning Tianlong Chen Sijia Liu Shiyu Chang Yu Cheng Lisa Amini Zhangyang Wang AAML 18 246 0 28 Mar 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 75 99 0 20 Mar 2020
When are Non-Parametric Methods Robust? Robi Bhattacharjee Kamalika Chaudhuri AAML 44 27 0 13 Mar 2020
SuperMix: Supervising the Mixing Data Augmentation Ali Dabouei Sobhan Soleymani Fariborz Taherkhani Nasser M. Nasrabadi 21 98 0 10 Mar 2020
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization Saehyung Lee Hyungyu Lee Sungroh Yoon AAML 163 113 0 05 Mar 2020
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness Ahmadreza Jeddi M. Shafiee Michelle Karg C. Scharfenberger A. Wong OOD AAML 72 63 0 02 Mar 2020
On Isometry Robustness of Deep 3D Point Cloud Models under Adversarial Attacks Yue Zhao Yuwei Wu Caihua Chen A. Lim 3DPC 16 70 0 27 Feb 2020
Improving Robustness of Deep-Learning-Based Image Reconstruction Ankit Raj Y. Bresler Bo-wen Li OOD AAML 29 50 0 26 Feb 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 47 788 0 26 Feb 2020