User Selection for Federated Learning in a Wireless Environment: A Process to Minimize the Negative Effect of Training Data Correlation and Improve Performance-Reference-Cited by-同舟云学术

User Selection for Federated Learning in a Wireless Environment: A Process to Minimize the Negative Effect of Training Data Correlation and Improve Performance

Published:2022-09 Issue:3 Volume:17 Page:26-33
ISSN:1556-6072
Container-title:IEEE Vehicular Technology Magazine
language:
Short-container-title:IEEE Veh. Technol. Mag.

Author:

Sun Chen¹,Wu Songtao²,Cui Tao³

Affiliation:

1. Head of the Wireless Network Research Department, Sony R&D Center, Beijing, China

2. Artificial Intelligence Research Department, Sony R&D Center, Beijing, China

3. Wireless Network Research Department, Sony R&D Center, Beijing, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/10209/9866621/09732307.pdf?arnumber=9732307

Reference15 articles.

1. Convergence Time Minimization of Federated Learning over Wireless Networks

2. Adaptive Federated Learning in Resource Constrained Edge Computing Systems

3. Stochastic Geometry for Modeling, Analysis, and Design of Multi-Tier and Cognitive Cellular Wireless Networks: A Survey

4. On Distances in Uniformly Random Networks

5. Discrete Exclusion Zone for Dynamic Spectrum Access Wireless Networks

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