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Oct, 2020
PrivNet：保护推荐算法中的私有特征的迁移学习
PrivNet: Safeguarding Private Attributes in Transfer Learning for Recommendation
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Guangneng Hu, Qiang Yang
TL;DR
本文提出了采用对抗训练的方式保护源域隐私的方法，在保护源域隐私前提下，通过转移学习提高目标域推荐系统的表现，实验证明该模型能够成功的保护源域隐私.
Abstract
transfer learning
is an effective technique to improve a target
recommender system
with the knowledge from a source domain. Existing research focuses on the recommendation performance of the target domain while i
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