Vector Quantization-Based Clustered Federated Learning With Global Feature Anchors for Improved Representation and Generalization.
- DOI
- 10.1109/tnnls.2025.3589186
- Published
- 2025-11-01
- Container
- IEEE Trans Neural Netw Learn Syst
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2025.3589186,
title = {Vector Quantization-Based Clustered Federated Learning With Global Feature Anchors for Improved Representation and Generalization.},
author = {Chen X and Zhang Y and Xu X and Hu D and Xu G.},
year = {2025},
journal = {IEEE Trans Neural Netw Learn Syst},
doi = {10.1109/tnnls.2025.3589186},
url = {https://doi.org/10.1109/tnnls.2025.3589186}
}RIS
TY - JOUR TI - Vector Quantization-Based Clustered Federated Learning With Global Feature Anchors for Improved Representation and Generalization. AU - Chen X AU - Zhang Y AU - Xu X AU - Hu D AU - Xu G. PY - 2025 JO - IEEE Trans Neural Netw Learn Syst DO - 10.1109/tnnls.2025.3589186 UR - https://doi.org/10.1109/tnnls.2025.3589186 ER -
APA
X, C., Y, Z., X, X., D, H., & G., X. (2025). Vector Quantization-Based Clustered Federated Learning With Global Feature Anchors for Improved Representation and Generalization.. IEEE Trans Neural Netw Learn Syst. https://doi.org/10.1109/tnnls.2025.3589186
Source records
- europe-pmc · retrieved 2026-09-25T18:17:22.847Z