A Comprehensive Survey on Split-Fed Learning: Methods, Innovations, and Future Directions

In this work we presented Split-Fed Learning (SFL), a new framework that combines the concepts of Federated Learning (FL) and Split Learning (SL), to provide privacy-aware and scalable training of machine learning models in settings with distributed data. With organizations needing more and more to...

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Bibliographic Details
Main Authors: Geetabai S. Hukkeri, R. H. Goudar, G. M. Dhananjaya, Vijayalaxmi N. Rathod, Shilpa Ankalaki
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/10909111/
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