Private, Efficient, and Accurate: Protecting Models Trained by Multi-party Learning with Differential Privacy

Wenqiang Ruan, Mingxin Xu, Wenjing Fang +3

Secure multi-party computation-based machine learning, referred to as MPL, has become an important technology to utilize data from multiple parties with privacy preservation. While…