Semi-supervised Learning in Distributed Split Learning Architecture and IoT Applications
Author:
Affiliation:
1. RWTH Aachen University,Chair of Information Theory and Data Analytics,Germany
Funder
Ministry of Education
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10091924/10091942/10092050.pdf?arnumber=10092050
Reference32 articles.
1. A Knowledge Transfer-based Semi-Supervised Federated Learning for IoT Malware Detection
2. Semi-Supervised Federated Learning for Travel Mode Identification From GPS Trajectories
3. Semi-Supervised Federated Learning with non-IID Data: Algorithm and System Design
4. Improving Semi-supervised Federated Learning by Reducing the Gradient Diversity of Models
5. Detection of traffic signs in real-world images: The German traffic sign detection benchmark
Cited by 2 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. An Efficient and Private ECG Classification System Using Split and Semi-Supervised Learning;IEEE Journal of Biomedical and Health Informatics;2023-09
2. Traffic Sign Classification for Autonomous Vehicles Using Split and Federated Learning Underlying 5G;IEEE Open Journal of Vehicular Technology;2023
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