Federated or Split? A Performance and Privacy Analysis of Hybrid Split and Federated Learning Architectures-Reference-Cited by-同舟云学术

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Federated or Split? A Performance and Privacy Analysis of Hybrid Split and Federated Learning Architectures

Published:2021-09 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE 14th International Conference on Cloud Computing (CLOUD)
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Author:

Turina Valeria,Zhang Zongshun,Esposito Flavio,Matta Ibrahim

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9581278/9582150/09582171.pdf?arnumber=9582171

Cited by 27 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Balancing privacy and performance in federated learning: A systematic literature review on methods and metrics;Journal of Parallel and Distributed Computing;2024-10

2. Federated Learning Models for Real-Time IoT: A Survey;2024 IEEE 27th International Symposium on Real-Time Distributed Computing (ISORC);2024-05-22

3. Edge-MSL: Split Learning on the Mobile Edge via Multi-Armed Bandits;IEEE INFOCOM 2024 - IEEE Conference on Computer Communications;2024-05-20

4. Split Federated Learning for 6G Enabled-Networks: Requirements, Challenges, and Future Directions;IEEE Access;2024

5. Machine Learning With Computer Networks: Techniques, Datasets, and Models;IEEE Access;2024

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