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Feb, 2019
差分隐私继续学习
Differentially Private Continual Learning
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Sebastian Farquhar, Yarin Gal
TL;DR
研究提出一种基于变分推理的差分隐私连续学习框架,该框架利用旧数据的差分隐私生成模型估计当前模型下旧数据的可能性,以解决机构删除历史数据的隐私问题所导致的神经网络记忆降解问题。
Abstract
catastrophic forgetting
can be a significant problem for institutions that must delete historic data for privacy reasons. For example, hospitals might not be able to retain patient data permanently. But
neural networks<
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