Communication-Efficient Design for Quantized Decentralized Federated Learning
(2024)
Journal Article
Chen, L., Liu, W., Chen, Y., & Wang, W. (2024). Communication-Efficient Design for Quantized Decentralized Federated Learning. IEEE Transactions on Signal Processing, 72, 1175-1188. https://doi.org/10.1109/TSP.2024.3363887
Decentralized federated learning (DFL) is a variant of federated learning, where edge nodes only communicate with their one-hop neighbors to learn the optimal model. However, as information exchange is restricted in a range of one-hop in DFL, ineffic... Read More about Communication-Efficient Design for Quantized Decentralized Federated Learning.