FedMcon: an adaptive aggregation method for federated learning via meta controller&
Regular Papers|Updated:2025-09-04
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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 EngineeringVol. 26, Issue 8, Pages: 1378-1393(2025)
Affiliations:
1.College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
2.School of Software Technology, Zhejiang University, Hangzhou 310027, China
3.School of Public Affairs, Zhejiang University, Hangzhou 310027, China
4.Academy of Social Governance, Zhejiang University, Hangzhou 310027, China
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:
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.
FedMcon: an adaptive aggregation method for federated learning via meta controller&