AFedAvg: communication-efficient federated learning aggregation with adaptive communication frequency and gradient sparse
Author:
Affiliation:
1. College of Artificial Intelligence, Nanjing Agricultural University, Nanjing, Jiangsu, China
Funder
the National Natural Science Foundation of China
High-level Personnel Project Funding of Jiangsu Province
Publisher
Informa UK Limited
Subject
Artificial Intelligence,Theoretical Computer Science,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/0952813X.2022.2079730
Reference40 articles.
1. Scalable inference in latent variable models
2. A Joint Learning and Communications Framework for Federated Learning Over Wireless Networks
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3. Limitations and Future Aspects of Communication Costs in Federated Learning: A Survey;Sensors;2023-08-23
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