Personalized Online Federated Learning for IoT/CPS: Challenges and Future Directions

Author:

Gogineni Vinay Chakravarthi1,Werner Stefan1,Gauthier Francois1,Huang Yih-Fang2,Kuh Anthony3

Affiliation:

1. Norwegian University of Science and Technology-NTNU,Norway

2. University of Notre Dame,USA

3. University of Hawai'i at Mānoa,USA

Funder

NSF

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Automotive Engineering

Cited by 6 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. Joint Age-Based Client Selection and Resource Allocation for Communication-Efficient Federated Learning Over NOMA Networks;IEEE Transactions on Communications;2024-01

2. Federated Recognition Architecture Based on Voting and Feedback Mechanisms for Accuracy Object Classification in Distributed Edge Intelligence Environment;IEEE Sensors Journal;2023-11-15

3. Distributed on-line anomaly detection using kernel methods;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31

4. Networked Personalized Federated Learning Using Reinforcement Learning;ICC 2023 - IEEE International Conference on Communications;2023-05-28

5. Personalized Graph Federated Learning With Differential Privacy;IEEE Transactions on Signal and Information Processing over Networks;2023

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