SR-FDIL: Synergistic Replay for Federated Domain-Incremental Learning-Reference-Cited by-同舟云学术

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SR-FDIL: Synergistic Replay for Federated Domain-Incremental Learning

Published:2024-11 Issue:11 Volume:35 Page:1879-1890
ISSN:1045-9219
Container-title:IEEE Transactions on Parallel and Distributed Systems
language:
Short-container-title:IEEE Trans. Parallel Distrib. Syst.

Author:

Li Yichen¹^ORCID,Xu Wenchao²^ORCID,Qi Yining¹^ORCID,Wang Haozhao¹^ORCID,Li Ruixuan¹^ORCID,Guo Song³^ORCID

Affiliation:

1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

2. Department of Computing, The Hong Kong Polytechnic University, Hong Kong, China

3. Department of Computer Science and Engineering, Hong Kong University of Science and Technology, Hong Kong, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/71/10670174/10620614.pdf?arnumber=10620614

Reference55 articles.

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

2. ATPFL: Automatic Trajectory Prediction Model Design under Federated Learning Framework

3. Federated Learning with Position-Aware Neurons

4. Privacy-Preserved Federated Learning for Autonomous Driving

5. Federated Learning for Healthcare Informatics

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