Decoupling Semantic and Structural Alignment for Cross-Domain Federated Learning
- DOI
- 10.1109/tnnls.2026.3732298
- Published
- 2026
- Container
- IEEE Transactions on Neural Networks and Learning Systems
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2026.3732298,
title = {Decoupling Semantic and Structural Alignment for Cross-Domain Federated Learning},
author = {Wenjie Yao and Suxia Zhu and Guanglu Sun and Ruidong Wang and Xinzhong Zhu and Yue Liu and Han Yu and Xiguang Wei},
year = {2026},
journal = {IEEE Transactions on Neural Networks and Learning Systems},
doi = {10.1109/tnnls.2026.3732298},
url = {https://doi.org/10.1109/tnnls.2026.3732298}
}RIS
TY - JOUR TI - Decoupling Semantic and Structural Alignment for Cross-Domain Federated Learning AU - Wenjie Yao AU - Suxia Zhu AU - Guanglu Sun AU - Ruidong Wang AU - Xinzhong Zhu AU - Yue Liu AU - Han Yu AU - Xiguang Wei PY - 2026 JO - IEEE Transactions on Neural Networks and Learning Systems DO - 10.1109/tnnls.2026.3732298 UR - https://doi.org/10.1109/tnnls.2026.3732298 ER -
APA
Yao, W., Zhu, S., Sun, G., Wang, R., Zhu, X., Liu, Y., Yu, H., & Wei, X. (2026). Decoupling Semantic and Structural Alignment for Cross-Domain Federated Learning. IEEE Transactions on Neural Networks and Learning Systems. https://doi.org/10.1109/tnnls.2026.3732298
Source records
- crossref · retrieved 2026-09-25T17:20:10.112Z