Joint Participant and Learning Topology Selection for Federated Learning in Edge Clouds-Reference-Cited by-同舟云学术

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Joint Participant and Learning Topology Selection for Federated Learning in Edge Clouds

Published:2024-08 Issue:8 Volume:35 Page:1456-1468
ISSN:1045-9219
Container-title:IEEE Transactions on Parallel and Distributed Systems
language:
Short-container-title:IEEE Trans. Parallel Distrib. Syst.

Author:

Wei Xinliang¹^ORCID,Ye Kejiang¹^ORCID,Shi Xinghua²,Xu Cheng-Zhong³^ORCID,Wang Yu²^ORCID

Affiliation:

1. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China

2. Department of Computer and Information Sciences, Temple University, Philadelphia, PA, USA

3. State Key Laboratory of IoTSC, Faculty of Science and Technology, University of Macau, Macau, China

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

https://ieeexplore.ieee.org/ielam/71/10557478/10557133-aam.pdf

Reference47 articles.

1. Communication-efficient learning of deep networks from decentralized data;McMahan

2. Robust and Communication-Efficient Federated Learning From Non-i.i.d. Data

3. Dynamic Sampling and Selective Masking for Communication-Efficient Federated Learning

4. Towards Efficient Synchronous Federated Training: A Survey on System Optimization Strategies

5. GossipFL: A Decentralized Federated Learning Framework With Sparsified and Adaptive Communication

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