Efficient Two-Step Adversarial Defense for Deep Neural Networks

ICLR 2019 Ting-Jui ChangYukun HePeng Li

In recent years, deep neural networks have demonstrated outstanding performance in many machine learning tasks. However, researchers have discovered that these state-of-the-art models are vulnerable to adversarial examples: legitimate examples added by small perturbations which are unnoticeable to human eyes... (read more)

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