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Adversarial examples: A survey

机译:对抗示例:调查

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摘要

Adversarial examples are a phenomenon that have gathered a lot of attention in recent studies. The fact that the addition of very small, but carefully crafted perturbations to the inputs of sophisticated and high performing machine learning models may cause them to make significant errors, is both fascinating and important. A survey of findings connected with adversarial examples is presented and discussed in this paper.
机译:对抗性例子是一种现象,在最近的研究中引起了很多关注。在复杂而高性能的机器学习模型的输入中添加很小但精心设计的扰动,可能会导致它们产生重大错误,这一事实既有趣又重要。本文提出并讨论了与对抗性例子相关的调查结果。

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