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While adversarial training can improve robust accuracy (against an adversary), it sometimes hurts standard accuracy (when there is no adversary).
Regression shrinkage and selection via the lasso
R. Tibshirani · 1996
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The elements of statistical learning , volume 1
J. Friedman, T. Hastie, and R. Tibshirani · 2001
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Semi-supervised self-training of object detection models
C. Rosenberg, M. Hebert, and H. Schneiderman · 2005
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus · 2014
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Explaining and harnessing adversarial examples
I. J. Goodfellow, J. Shlens, and C. Szegedy · 2015
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CVXPY: A Python-embedded modeling language for convex optimization
S. Diamond and S. Boyd · 2016
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Wide residual networks
S. Zagoruyko and N. Komodakis · 2016
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Adversarial risk bounds for binary classification via function transformation
J. Khim and P. Loh · 2018
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu · 2018
Cited alongside, same era.
Adversarially robust generalization requires more data
L. Schmidt, S. Santurkar, D. Tsipras, K. Talwar, and A. Madry · 2018
Cited alongside, same era.
Rademacher complexity for adversarially robust generalization
D. Yin, K. Ramchandran, and P. Bartlett · 2018
Cited alongside, same era.
Unlabeled data improves adversarial robustness
Y. Carmon, A. Raghunathan, L. Schmidt, P. Liang, and J. C. Duchi · 2019
Cited alongside, same era.
Robustness to adversarial perturbations in learning from incomplete data
A. Najafi, S. Maeda, M. Koyama, and T. Miyato · 2019
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Adversarial robustness may be at odds with simplicity
P. Nakkiran · 2019
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Robustness may be at odds with accuracy
D. Tsipras, S. Santurkar, L. Engstrom, A. Turner, and A. Madry · 2019
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Are labels required for improving adversarial robustness?
J. Uesato, J. Alayrac, P. Huang, R. Stanforth, A. Fawzi, and P. Kohli · 2019
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Adversarially robust generalization just requires more unlabeled data
R. Zhai, T. Cai, D. He, C. Dan, K. He, J. Hopcroft, and L. Wang · 2019
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VC classes are adversarially robustly learnable, but only improperly
O. Montasser, S. Hanneke, and N. Srebro · 2019
Cited alongside, same era.
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Theoretically principled trade-off between robustness and accuracy
H. Zhang, Y. Yu, J. Jiao, E. P. Xing, L. E. Ghaoui, and M. I. Jordan · 2019
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