Peer-reviewedCC BY-NC-ND 4.0Scientific Reports
An adaptive federated few-shot learning method with intelligent device selection
Related
- Intelligent defense at the edge: a comprehensive survey of federated learning, TinyML and explainable AI for intrusion detection in IoT and IIoT ecosystems
- PoSFed: stake-aware validator selection and update filtering for blockchain-coordinated healthcare federated learning
- Joint Vehicle Selection and Resource Allocation for Hierarchical Federated Learning in Internet of Vehicles
- Lightweight adaptive split federated learning for patient-independent ECG arrhythmia classification
- Adaptive federated ensemble learning with hyperparameter optimization for distributed healthcare IoT
BibTeX
@article{tavassolian2026adaptive,
title = {{An adaptive federated few-shot learning method with intelligent device selection}},
author = {Fazeleh Tavassolian and Mahdi Abbasi and Atefeh Salimi Shahraki and Abbas Ramazani and Reihaneh Tarlani},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-73779-y},
url = {https://www.nature.com/articles/s41598-026-73779-y},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - An adaptive federated few-shot learning method with intelligent device selection
AU - Fazeleh Tavassolian
AU - Mahdi Abbasi
AU - Atefeh Salimi Shahraki
AU - Abbas Ramazani
AU - Reihaneh Tarlani
PY - 2026
DA - 2026/10/03
JO - Scientific Reports
DO - 10.1038/s41598-026-73779-y
UR - https://www.nature.com/articles/s41598-026-73779-y
SN - 2045-2322
ER -