Joint Client Selection and Bandwidth Allocation of Wireless Federated Learning by Deep Reinforcement Learning
Author:
Affiliation:
1. School of Computer Science and Technology, East China Normal University (ECNU), Shanghai, China
Funder
Natural Science Foundation of Shanghai
Natural Science Foundation of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/4629386/10422891/10381828.pdf?arnumber=10381828
Reference44 articles.
1. DeepThings: Distributed Adaptive Deep Learning Inference on Resource-Constrained IoT Edge Clusters
2. Communication-efficient learning of deep networks from decentralized data;McMahan
3. Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanism
4. Federated Learning over Wireless Networks: Optimization Model Design and Analysis
5. Client Scheduling and Resource Management for Efficient Training in Heterogeneous IoT-Edge Federated Learning
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