On the Generalization Properties of Adversarial Training

15 August 2020

Papers citing "On the Generalization Properties of Adversarial Training"

38 / 38 papers shown

Title
Efficient Optimization Algorithms for Linear Adversarial Training Antônio H. Ribeiro Thomas B. Schon Dave Zahariah Francis Bach AAML 64 1 0 16 Oct 2024
On the Convergence and Robustness of Adversarial Training Yisen Wang Xingjun Ma James Bailey Jinfeng Yi Bowen Zhou Quanquan Gu AAML 244 346 0 15 Dec 2021
On Connections between Regularizations for Improving DNN Robustness Yiwen Guo Long Chen Yurong Chen Changshui Zhang AAML 34 14 0 04 Jul 2020
Smooth Adversarial Training Cihang Xie Mingxing Tan Boqing Gong Alan Yuille Quoc V. Le OOD 54 152 0 25 Jun 2020
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack Methods Kyungmi Lee A. Chandrakasan ELM AAML 29 3 0 01 Jun 2020
Feature Purification: How Adversarial Training Performs Robust Deep Learning Zeyuan Allen-Zhu Yuanzhi Li MLT AAML 59 149 0 20 May 2020
Adversarial Weight Perturbation Helps Robust Generalization Dongxian Wu Shutao Xia Yisen Wang OOD AAML 32 17 0 13 Apr 2020
Towards Practical Lottery Ticket Hypothesis for Adversarial Training Bai Li Shiqi Wang Yunhan Jia Yantao Lu Zhenyu Zhong Lawrence Carin Suman Jana AAML 110 14 0 06 Mar 2020
Overfitting in adversarially robust deep learning Leslie Rice Eric Wong Zico Kolter 73 796 0 26 Feb 2020
The Curious Case of Adversarially Robust Models: More Data Can Help, Double Descend, or Hurt Generalization Yifei Min Lin Chen Amin Karbasi AAML 68 69 0 25 Feb 2020
Precise Tradeoffs in Adversarial Training for Linear Regression Adel Javanmard Mahdi Soltanolkotabi Hamed Hassani AAML 32 106 0 24 Feb 2020
Over-parameterized Adversarial Training: An Analysis Overcoming the Curse of Dimensionality Yi Zhang Orestis Plevrakis S. Du Xingguo Li Zhao Song Sanjeev Arora 96 51 0 16 Feb 2020
More Data Can Expand the Generalization Gap Between Adversarially Robust and Standard Models Lin Chen Yifei Min Mingrui Zhang Amin Karbasi OOD 53 64 0 11 Feb 2020
Fast is better than free: Revisiting adversarial training Eric Wong Leslie Rice J. Zico Kolter AAML OOD 122 1,167 0 12 Jan 2020
Convergence of Adversarial Training in Overparametrized Neural Networks Ruiqi Gao Tianle Cai Haochuan Li Liwei Wang Cho-Jui Hsieh Jason D. Lee AAML 82 107 0 19 Jun 2019
Adversarial Training Can Hurt Generalization Aditi Raghunathan Sang Michael Xie Fanny Yang John C. Duchi Percy Liang 57 241 0 14 Jun 2019
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers Hadi Salman Greg Yang Jungshian Li Pengchuan Zhang Huan Zhang Ilya P. Razenshteyn Sébastien Bubeck AAML 57 544 0 09 Jun 2019
Adversarially Robust Generalization Just Requires More Unlabeled Data Runtian Zhai Tianle Cai Di He Chen Dan Kun He John E. Hopcroft Liwei Wang 61 156 0 03 Jun 2019
Robustness to Adversarial Perturbations in Learning from Incomplete Data Amir Najafi S. Maeda Masanori Koyama Takeru Miyato OOD 64 130 0 24 May 2019
Adversarial Robustness vs Model Compression, or Both? Shaokai Ye Kaidi Xu Sijia Liu Jan-Henrik Lambrechts Huan Zhang Aojun Zhou Kaisheng Ma Yanzhi Wang Xue Lin AAML 44 164 0 29 Mar 2019
Surprises in High-Dimensional Ridgeless Least Squares Interpolation Trevor Hastie Andrea Montanari Saharon Rosset Robert Tibshirani 126 737 0 19 Mar 2019
Two models of double descent for weak features M. Belkin Daniel J. Hsu Ji Xu 80 375 0 18 Mar 2019
Using Pre-Training Can Improve Model Robustness and Uncertainty Dan Hendrycks Kimin Lee Mantas Mazeika NoLa 62 726 0 28 Jan 2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruosong Wang MLT 137 966 0 24 Jan 2019
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du Jason D. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 141 1,133 0 09 Nov 2018
Rademacher Complexity for Adversarially Robust Generalization Dong Yin Kannan Ramchandran Peter L. Bartlett AAML 69 258 0 29 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 151 1,261 0 04 Oct 2018
Adversarially Robust Generalization Requires More Data Ludwig Schmidt Shibani Santurkar Dimitris Tsipras Kunal Talwar Aleksander Madry OOD AAML 116 786 0 30 Apr 2018
The Robust Manifold Defense: Adversarial Training using Generative Models A. Jalal Andrew Ilyas C. Daskalakis A. Dimakis AAML 50 174 0 26 Dec 2017
Certifying Some Distributional Robustness with Principled Adversarial Training Aman Sinha Hongseok Namkoong Riccardo Volpi John C. Duchi OOD 81 858 0 29 Oct 2017
Evasion Attacks against Machine Learning at Test Time Battista Biggio Igino Corona Davide Maiorca B. Nelson Nedim Srndic Pavel Laskov Giorgio Giacinto Fabio Roli AAML 101 2,142 0 21 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 231 11,962 0 19 Jun 2017
Crafting Adversarial Input Sequences for Recurrent Neural Networks Nicolas Papernot Patrick McDaniel A. Swami Richard E. Harang AAML GAN SILM 32 455 0 28 Apr 2016
The Limitations of Deep Learning in Adversarial Settings Nicolas Papernot Patrick McDaniel S. Jha Matt Fredrikson Z. Berkay Celik A. Swami AAML 66 3,947 0 24 Nov 2015
DeepFool: a simple and accurate method to fool deep neural networks Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi P. Frossard AAML 98 4,878 0 14 Nov 2015
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 185 14,831 1 21 Dec 2013
Least squares after model selection in high-dimensional sparse models A. Belloni Victor Chernozhukov 199 222 0 31 Dec 2009
Simultaneous analysis of Lasso and Dantzig selector Peter J. Bickel Yaácov Ritov Alexandre B. Tsybakov 327 2,527 0 07 Jan 2008