Client-Edge-Cloud Hierarchical Federated Learning联邦学习(云 -边-端)模型笔记 摘要 摘要--联合学习是一个协作式的机器学习框架,用于训练深度学习模型而不需要访问客户的私人数据。以前的工作假设在云端或边缘有一个中央参数服务器。云服务器可以访问更多的数据,但有过多的通信开销和较长的延迟,而边缘服务器享有与...
In this paper, we present the first personalized federated learning algorithm based on the client-edge-cloud structure. The edge server is responsible for model personalization and employs a learnable mixing parameter to mix the local model and the global model. We also utilize two learnable ...
Mobile edge computing aims to deploy mobile applications at the edge of wireless networks. Federated learning in mobile edge computing is a forward-looking distributed framework for deploying deep learning algorithms in many application scenarios. One challenge of federated learning in mobile edge computin...
Journal of Cloud Computing (2024) 13:161 https://doi.org/10.1186/s13677-024-00721-w Journal of Cloud Computing: Advances, Systems and Applications RESEARCH Open Access Personalized client‑edge‑cloud hierarchical federated learning in mobile edge computing Chunmei Ma1, Xiangqian Li1, ...
Implementation of HierFAVG algorithm inClient-Edge-Cloud Hierarchical Federated Learningwith Pytorch. For running HierFAVG with mnist and lenet: python3 hierfavg --dataset mnist --model lenet --num_clients 50 --num_edges 5 --frac 1 --num_local_update 60 --num_edge_aggregation 1 --num...
Implementation of HierFAVG algorithm inClient-Edge-Cloud Hierarchical Federated Learningwith Pytorch. For running HierFAVG with mnist and lenet: python3 hierfavg --dataset mnist --model lenet --num_clients 50 --num_edges 5 --frac 1 --num_local_update 60 --num_edge_aggregation 1 --num...