Decentralized Federated Learning with Distributed Aggregation Weight Optimization.
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DOI: 10.1109/tpami.2025.3640709
Abstract: Decentralized federated learning (DFL) is an emerging paradigm to enable edge devices collaboratively training a learning model using a device-to-device (D2D) communication manner without the coordination of a parameter server (PS). Aggregation weights, also known… read more here.
Keywords: dfl; aggregation weights; federated learning; aggregation ... See more keywords