Intriguing Properties of Adversarial Examples

ICLR 2018 Ekin D. CubukBarret ZophSamuel S. SchoenholzQuoc V. Le

It is becoming increasingly clear that many machine learning classifiers are vulnerable to adversarial examples. In attempting to explain the origin of adversarial examples, previous studies have typically focused on the fact that neural networks operate on high dimensional data, they overfit, or they are too linear... (read more)

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