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PFL-AP: Personalized Federated Learning With Adaptive Affine Calibration and Prototype-Driven Knowledge Fusion for Non-IID Data

Personalized federated learning (PFL) based on model decoupling has emerged as a prominent paradigm for mitigating statistical heterogeneity. However, most existing methods rely on static or oversimplified local representations, neglecting the severe feature misalignment during global aggregation. This inevitably preci...

Wei Liu, Rui Wang, Bin Wang et al. · 0 citations

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