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Adversarial training was introduced as a way to improve the robustness of deep learning models to adversarial attacks.
The at&t database of faces, 2002
A. L. Cambridge · 2002
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Learning multiple layers of features from tiny images
A. Krizhevsky and G. Hinton · 2009
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Convolutional deep belief networks on cifar-10
A. Krizhevsky and G. Hinton · 2010
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Model inversion attacks that exploit confidence information and basic countermeasures
M. Fredrikson, S. Jha, and T. Ristenpart · 2015
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Explaining and harnessing adversarial examples. corr (2015)
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2015
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Deepdream-a code example for visualizing neural networks
A. Mordvintsev, C. Olah, and M. Tyka · 2015
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Visualizing deep convolutional neural networks using natural pre-images
A. Mahendran and A. Vedaldi · 2016
Cited alongside, same era.
Distillation as a defense to adversarial perturbations against deep neural networks
N. Papernot, P. McDaniel, X. Wu, S. Jha, and A. Swami · 2016
Cited alongside, same era.
Stealing machine learning models via prediction apis
F. Tramèr, F. Zhang, A. Juels, M. K. Reiter, and T. Ristenpart · 2016
Cited alongside, same era.
S. Zagoruyko and N. Komodakis · 2016
Cited alongside, same era.
Adversarial examples are not easily detected: Bypassing ten detection methods
N. Carlini and D. Wagner · 2017
Cited alongside, same era.
Deep models under the gan: information leakage from collaborative deep learning
Conditional image synthesis with auxiliary classifier gans
A. Odena, C. Olah, and J. Shlens · 2017
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Membership inference attacks against machine learning models
R. Shokri, M. Stronati, C. Song, and V. Shmatikov · 2017
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Generative poisoning attack method against neural networks
C. Yang, Q. Wu, H. Li, and Y. Chen · 2017
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Defense against adversarial attacks using high-level representation guided denoiser
F. Liao, M. Liang, Y. Dong, T. Pang, X. Hu, and J. Zhu · 2018
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A. Salem, Y. Zhang, M. Humbert, M. Fritz, and M. Backes · 2018
Later among the works it cites.
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B. Hitaj, G. Ateniese, and F. Perez-Cruz · 2017
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2017
Cited alongside, same era.
Robustness may be at odds with accuracy
D. Tsipras, S. Santurkar, L. Engstrom, A. Turner, and A. Madry · 2018
Later among the works it cites.