Personalized Fair Split Learning for Resource-Constrained Internet of Things

• Published in: Sensors (Basel, Switzerland) Vol. 24; no. 1; p. 88
• Main Authors: Chen, Haitian, Chen, Xuebin, Peng, Lulu, Bai, Yuntian
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 23.12.2023; MDPI
• Subjects: Big Data; Collaboration; collaborative fairness; Communication; Cooperation; data heterogeneity; Datasets; Equipment and supplies; federated learning; Internet of Things; personalized model; Privacy; Propagation; Sensors; split learning; Teaching; Teaching methods; Training; personalized model; split learning; collaborative fairness; Internet of Things; data heterogeneity; federated learning

With the flourishing development of the Internet of Things (IoT), federated learning has garnered significant attention as a distributed learning method aimed at preserving the privacy of participant data. However, certain IoT devices, such as sensors, face challenges in effectively employing conven...