Adversarial Examples can be Effective Data Augmentation for Unsupervised
Machine Learning

Adversarial Examples can be Effective Data Augmentation for Unsupervised Machine Learning

2 March 2021

Papers citing "Adversarial Examples can be Effective Data Augmentation for Unsupervised Machine Learning"

15 / 15 papers shown

Title
Non-convex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances Meisam Razaviyayn Tianjian Huang Songtao Lu Maher Nouiehed Maziar Sanjabi Mingyi Hong 53 114 0 15 Jun 2020
Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization Sicheng Zhu Xiao Zhang David Evans SSL OOD 47 27 0 26 Feb 2020
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 119 751 0 31 May 2019
Disentangling Adversarial Robustness and Generalization David Stutz Matthias Hein Bernt Schiele AAML OOD 251 280 0 03 Dec 2018
Unsupervised representation learning using convolutional and stacked auto-encoders: a domain and cross-domain feature space analysis G. B. Cavallari Leo Sampaio Ferraz Ribeiro M. Ponti SSL OOD DRL 28 29 0 01 Nov 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 93 1,776 0 30 May 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 187 3,180 0 01 Feb 2018
Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach Tsui-Wei Weng Huan Zhang Pin-Yu Chen Jinfeng Yi D. Su Yupeng Gao Cho-Jui Hsieh Luca Daniel AAML 76 467 0 31 Jan 2018
Demystifying MMD GANs Mikolaj Binkowski Danica J. Sutherland Michael Arbel Arthur Gretton EGVM 118 1,490 0 04 Jan 2018
Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning Battista Biggio Fabio Roli AAML 98 1,407 0 08 Dec 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 269 12,029 0 19 Jun 2017
Adversarial Examples Are Not Easily Detected: Bypassing Ten Detection Methods Nicholas Carlini D. Wagner AAML 118 1,854 0 20 May 2017
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 226 8,548 0 16 Aug 2016
Adversarial Autoencoders Alireza Makhzani Jonathon Shlens Navdeep Jaitly Ian Goodfellow Brendan J. Frey GAN 84 2,226 0 18 Nov 2015
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 239 14,893 1 21 Dec 2013

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