Latent Information Sharing for Accelerating Federated Learning
Federated learning (FL) is a communication-efficient distributed learning paradigm. However, client drift remains one of the most critical challenges, hindering the efficient training of a global model. In this study, we propose a novel latent information sharing scheme that directly mitigates data heterogeneity across...
Seung-Jun Lee, Ensieh Khazaei, Dimitrios Hatzinakos et al.
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