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Asynchronous Federated Learning with Incentive Mechanism Based on Contract Theory
To address the challenges posed by the heterogeneity inherent in federated learning (FL) and to attract high-quality clients, various incentive mechanisms have been employed.
Semi-Asynchronous Federated Edge Learning Mechanism via Over-the-air Computation
However, existing FEEL systems with AirComp scheme often employ traditional synchronous aggregation mechanisms for local model aggregation in each global round, which suffer from the stragglers issues.
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