A3T: Adversarially Augmented Adversarial TrainingEI

    Cited by: 3|Bibtex|66|

    arXiv: Learning, Volume abs/1801.040552018,

    Abstract:

    Recent research showed that deep neural networks are highly sensitive to so-called adversarial perturbations, which are tiny perturbations of the input data purposely designed to fool a machine learning classifier. Most classification models, including deep learning models, are highly vulnerable to adversarial attacks. In this work, we in...More
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