论文笔记——Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
论文笔记——Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge 本文提出了一种基于边缘计算的协议来改进联邦学习算法。算法 由服务器和基站（BS）组成的位于无线网络中的特定MEC平台管理服务器和客户端的行为。服务器 经过MEC operator 对客户端进行选择。网络 首先，随机选取必
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相关文章
- 1. 论文笔记——Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- 2. Client Selection for Federated Learning with Heterogeneous Resources in Mobile Edge
- 3. 论文笔记Client-Edge-Cloud Hierarchical Federated Learning
- 4. 论文笔记——Federated learning framework for mobile edge computing networks
- 5. Federated Learning in Mobile Edge Networks: AComprehensive Survey(翻译)
- 6. Differentially Private Asynchronous Federated Learning for Mobile Edge Computing in Urban Informatic
- 7. Federated Learning with Non-IID Data 论文笔记
- 8. 论文笔记——Fair Resource Allocation in Federated Learning
- 9. Secure Federated Transfer Learning（论文笔记）
- 10. 论文：Learning Matching Models with Weak Supervision for Response Selection in Retrieval-based Chatbots