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Robust and Sparse Personalized Federated Learning via Gamma-Divergence
To address the challenges of statistical heterogeneity across clients and within-client data contamination in federated learning, we propose a robust and sparse personalized federated learning method based on the gamma-divergence, termed Gamma-PFL. Specifically, we combine a loss function based on t
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