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Dec, 2019
对抗鲁棒性基准测试
Benchmarking Adversarial Robustness
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Yinpeng Dong, Qi-An Fu, Xiao Yang, Tianyu Pang, Hang Su...
TL;DR
本研究旨在建立一个全面、严谨、连贯的标准来评估对抗性鲁棒性,通过两个鲁棒性曲线作为公正的评估标准来进行大规模实验,全面掌握攻击与防御方法的表现并得出重要结论和未来研究的启示。
Abstract
deep neural networks
are vulnerable to
adversarial examples
, which becomes one of the most important research problems in the development of deep learning. While a lot of efforts have been made in recent years, i
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