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Jiabei Liu

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2025

FedRAM: Federated Reweighting and Aggregation for Multi-Task Learning

FedRAM is proposed, a three-step framework that progressively updates two scalar hyperparameters: the task importance weight and the client aggregation coefficient, where the proxy model serves as an intermediate between the local reference model and the global agent model.

Fan Wu, Xinyu Yan, Jiabei Liu et al. · 0 citations

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