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Abstract: The adoption of deep learning models in V2X scenarios has boosted computing demands in edge computing, while concept drift requires frequent model retraining, further increasing computing ...

Abstract: Federated learning (FL) has emerged as a pivotal approach for edge-based distributed machine learning, yet it faces significant challenges due to the constrained capacities and heterogeneity ...