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Aug, 2020
有限数据下消除神经网络中基于后门的水印
Removing Backdoor-Based Watermarks in Neural Networks with Limited Data
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Xuankai Liu, Fengting Li, Bihan Wen, Qi Li
TL;DR
本文介绍了一种基于小样本数据的去水印方法,使用数据增强和特征空间中正常和扰动数据的分布对齐相结合,有效地去除深度模型中的水印,并不影响深度模型性能。
Abstract
deep neural networks
have been widely applied and achieved great success in various fields. As training deep models usually consumes massive data and computational resources,
trading
the trained deep models is hi
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