Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective

26 Feb 2020 Yilun Jin Xiguang Wei Yang Liu Qiang Yang

Federated Learning (FL) proposed in recent years has received significant attention from researchers in that it can bring separate data sources together and build machine learning models in a collaborative but private manner. Yet, in most applications of FL, such as keyboard prediction, labeling data requires virtually no additional efforts, which is not generally the case... (read more)

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