Toward Communication-Learning Trade-Off for Federated Learning at the Network Edge
Author:
Affiliation:
1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China
Funder
National Key Research and Development Program of China
BUPT Innovation and Entrepreneurship Support Program
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Modeling and Simulation
Link
http://xplorestaging.ieee.org/ielx7/4234/9854924/09772760.pdf?arnumber=9772760
Reference11 articles.
1. Client Selection and Bandwidth Allocation in Wireless Federated Learning Networks: A Long-Term Perspective
2. Cost-Effective Federated Learning Design
3. Adaptive Network Pruning for Wireless Federated Learning
4. Joint Resource Allocation for Efficient Federated Learning in Internet of Things Supported by Edge Computing
5. A General Upper Bound to Evaluate Packet Error Rate over Quasi-Static Fading Channels
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