A Practical Privacy-preserving Method in Federated Deep Learning

23 Feb 2020 Yan Feng Xue Yang Weijun Fang Shu-Tao Xia Xiaohu Tang Jun Shao Tao Xiong

Although federated learning improves privacy of training data by exchanging model updates rather than raw data, many research results show that sharing the model updates may still involve risks. To alleviate this problem, many privacy-preserving techniques have been introduced to federated learning... (read more)

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