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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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10909111/ |
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