FedGMI applies VAEs as density estimators in federated learning to infer mixture proportions of shared distributions for structured personalization under data heterogeneity.
An Efficient Framework for Clustered Federated Learning
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FedGMI: Generative Model-Driven Federated Learning for Probabilistic Mixture Inference
FedGMI applies VAEs as density estimators in federated learning to infer mixture proportions of shared distributions for structured personalization under data heterogeneity.