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FedMcon: an adaptive aggregation method for federated learning via meta controller&
Regular Papers | Updated:2025-09-04
    • FedMcon: an adaptive aggregation method for federated learning via meta controller&

    • FedMcon:一种通过元控制器实现的联邦学习自适应聚合方法
    • In the field of federated learning, a new aggregation method called FedMcon has been proposed. Expert researchers have introduced a learnable controller trained on a small proxy dataset and served as an aggregator to learn how to adaptively aggregate heterogeneous local models into a better global model toward the desired objective. This provides solutions to solve the problem of hindered convergence and compromised generalization in federated learning.
    • Frontiers of Information Technology & Electronic Engineering   Vol. 26, Issue 8, Pages: 1378-1393(2025)
    • DOI:10.1631/FITEE.2400530    

      CLC: TP39
    • Received:20 June 2024

      Revised:2024-12-15

      Published:2025-08

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  • Tao SHEN, Zexi LI, Ziyu ZHAO, et al. FedMcon: an adaptive aggregation method for federated learning via meta controller&[J]. Frontiers of Information Technology & Electronic Engineering, 2025, 26(8): 1378-1393. DOI: 10.1631/FITEE.2400530.

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