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Dan Wang

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Jul 2026

SeqFedRPC: Sequential Federated Learning With Regularized Parameter Clustering

This work proposes SeqFedRPC, a novel model decoupling based SFL framework with regularized parameter clustering, and employs a clustering‐based scheme to adaptively decouple the model parameters into shared and personalized subsets, thereby addressing the challenge of non‐IID data.

Peng Mao, Tian Du, Zhonghui Wu et al. · 0 citations