Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness
- DOI
- 10.1109/tpami.2026.3689213
- Published
- 2026-09
- Container
- IEEE Transactions on Pattern Analysis and Machine Intelligence
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tpami.2026.3689213,
title = {Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness},
author = {Renqiang Luo and Huafei Huang and Shuo Yu and Fengqi Yu and Feng Xia and Sajal K. Das and Chengqi Zhang},
year = {2026},
journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
doi = {10.1109/tpami.2026.3689213},
url = {https://doi.org/10.1109/tpami.2026.3689213}
}RIS
TY - JOUR TI - Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness AU - Renqiang Luo AU - Huafei Huang AU - Shuo Yu AU - Fengqi Yu AU - Feng Xia AU - Sajal K. Das AU - Chengqi Zhang PY - 2026 JO - IEEE Transactions on Pattern Analysis and Machine Intelligence DO - 10.1109/tpami.2026.3689213 UR - https://doi.org/10.1109/tpami.2026.3689213 ER -
APA
Luo, R., Huang, H., Yu, S., Yu, F., Xia, F., Das, S. K., & Zhang, C. (2026). Utility-Preserving Federated Graph Learning With Dual-Perspective Fairness. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2026.3689213
Source records
- crossref · retrieved 2026-09-25T13:32:05.729Z