Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much AccuracyEI

    Alex Lamb
    Alex Lamb
    Vikas Verma
    Vikas Verma
    Juho Kannala
    Juho Kannala
    Cited by: 0|Bibtex|54|

    Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security, pp. 95-103, 2019.

    Keywords:
    adversarial robustness interpolation based training manifold mixup mixup neural networksview more (1+)

    Abstract:

    Adversarial robustness has become a central goal in deep learning, both in theory and in practice. However, successful methods to improve the adversarial robustness (such as adversarial training) greatly hurt generalization performance on the unperturbed data. This could have a major impact on how achieving adversarial robustness affects ...More
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