A composition–decomposition based federated learning
Chaoli Sun,
Xiaojun Wang,
Junwei Ma
et al.
Abstract:Federated learning has been shown to be efficient for training a global model without needing to collect all data from multiple entities to the centralized server. However, the model performance, communication traffic, and data privacy and security are still the focus of federated learning after it has been developed. In this paper, a composition–decomposition based federated learning, denoted as CD-FL, is proposed. In the CD-FL approach, the global model, composed of K sub-models with the same framework, will… Show more
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