Robust Federated Learning Against Data Poisoning: A Split Learning-Based Approach Evaluated on Various Aggregation Techniques
- DOI
- 10.1109/healthcom60970.2024.10880725
- Published
- 2024-11-18
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- Not recorded
- Publisher
- IEEE
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1109/healthcom60970.2024.10880725,
title = {Robust Federated Learning Against Data Poisoning: A Split Learning-Based Approach Evaluated on Various Aggregation Techniques},
author = {Abdelkader Tounsi and Osman Salem and Ahmed Mehaoua},
year = {2024},
doi = {10.1109/healthcom60970.2024.10880725},
url = {https://doi.org/10.1109/healthcom60970.2024.10880725}
}RIS
TY - JOUR TI - Robust Federated Learning Against Data Poisoning: A Split Learning-Based Approach Evaluated on Various Aggregation Techniques AU - Abdelkader Tounsi AU - Osman Salem AU - Ahmed Mehaoua PY - 2024 DO - 10.1109/healthcom60970.2024.10880725 UR - https://doi.org/10.1109/healthcom60970.2024.10880725 ER -
APA
Tounsi, A., Salem, O., & Mehaoua, A. (2024). Robust Federated Learning Against Data Poisoning: A Split Learning-Based Approach Evaluated on Various Aggregation Techniques. https://doi.org/10.1109/healthcom60970.2024.10880725
Source records
- hal · retrieved 2026-09-27T05:09:41.881Z