FedHCL: Hierarchical Cluster Fine-Grained Prototype Contrastive Learning for Multifeature Distributions and Model Heterogeneity in FL
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DOI: 10.1109/jiot.2025.3600750
Abstract: Recently, federated learning (FL) has gained widespread attention for its ability to support multiple clients in collaborative learning while preserving data privacy. However, existing solutions mainly focus on the issue of the client’s private data… read more here.
Keywords: grained prototype; fine grained; model heterogeneity;