FedGTA: Topology-aware Averaging for Federated Graph Learning
Summary: FedGTA introduces topology-aware federated aggregation using local smoothing confidence and mixed-neighbor features, rather than vision-oriented optimization. It delivers personalized, scalable FGL with state-of-the-art results, including on ogbn-papers100M. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Xunkai Li (Beijing Institute of Technology)
- 2. Zhengyu Wu (Beijing Institute of Technology)
- 3. Wentao Zhang (HEC Montreal; Mila)
- 4. Yinlin Zhu (Sun Yat-Sen University)
- 5. Rong-Hua Li (Beijing Institute of Technology)
- 6. Guoren Wang (Beijing Institute of Technology)
BibTeX Citation
@article{li_vldb24,
title = {{FedGTA: Topology-aware Averaging for Federated Graph Learning}},
author = {Li, Xunkai and Wu, Zhengyu and Zhang, Wentao and Zhu, Yinlin and Li, Rong-Hua and Wang, Guoren},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {1},
pages = {41--50},
doi = {10.14778/3617838.3617842},
url = {https://doi.org/10.14778/3617838.3617842},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 2 of 2 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,226 | OpenFGL: A Comprehensive Benchmark for Federated Graph Learning | 2025 | VLDB | 4.9793485e-05 |
| 11,501 | NPA: Improving Large-scale Graph Neural Networks with Non-parametric Attention | 2024 | SIGMOD | 4.9793485e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,124 | SCARA: Scalable Graph Neural Networks with Feature-Oriented Optimization | 2022 | VLDB | 6.2624516e-05 |
| 6,028 | A Scalable AutoML Approach Based on Graph Neural Networks | 2022 | VLDB | 5.9110992e-05 |
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