Adaptive Clustered Federated Learning for Clients with Time-Varying Interests-Reference-Cited by-同舟云学术

Adaptive Clustered Federated Learning for Clients with Time-Varying Interests

Published:2022-06-10 Issue: Volume: Page:
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Container-title:2022 IEEE/ACM 30th International Symposium on Quality of Service (IWQoS)
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Author:

Wang Ne¹,Zhou Ruiting¹,Su Lina¹,Fang Guang¹,Li Zongpeng²

Affiliation:

1. Wuhan University,School of Computer Science,China

2. Tsinghua University,Insititue for Network Sciences and Cyberspace,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9812862/9812863/09812926.pdf?arnumber=9812926

Reference30 articles.

1. An Efficiency-boosting Client Selection Scheme for Federated Learning with Fairness Guarantee

2. ClusterFL

3. Clustered sampling: Low-variance and improved representativity for clients selection in federated learning;fraboni;Proceedings of the 38th International Conference on Machine Learning,2021

4. Oort: Efficient federated learning via guided participant selection;lai;Proc of USENIX OSDI,2021

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