FedGVD: Efficient Federated Graph Learning via Unidirectional Distillation with Dynamic Virtual Nodes.
Zhehao Dai|Guojiang Shen|Yuyue Hu|Jiaxin Du|Xiao Han|Xiangjie Kong
| Anthology ID: | DBLP:conf/cikm/DaiSHD0025 |
|---|---|
| Volume: | Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025 |
| Year: | 2025 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 488-497 |
| URL: | https://doi.org/10.1145/3746252.3761338 |
| DOI: | https://doi.org/10.1145/3746252.3761338 |
| DBLP: | conf/cikm/DaiSHD0025 |
| BibTeX: |
@inproceedings{dai-2025-fedgvd,
author = {Zhehao Dai and
Guojiang Shen and
Yuyue Hu and
Jiaxin Du and
Xiao Han and
Xiangjie Kong},
editor = {Meeyoung Cha and
Carl Yang and
Senjuti Basu Roy and
Chanyoung Park and
Zhenhui Jessie Li and
Noseong Park and
Carl Yang and
Senjuti Basu Roy and
Zhenhui Jessie Li and
Jaap Kamps and
Kijung Shin and
Bryan Hooi and
Lifang He},
title = {{FedGVD: Efficient Federated Graph Learning via Unidirectional Distillation with Dynamic Virtual Nodes}},
booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}},
pages = {488--497},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3746252.3761338},
doi = {https://doi.org/10.1145/3746252.3761338}
}