FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph
Federated Learning

FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning

22 April 2024

Yinlin Zhu

Zhengyu Wu

Papers citing "FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning"

5 / 5 papers shown

Title
Rethinking Federated Graph Learning: A Data Condensation Perspective Hao Zhang Xunkai Li Y. X. Zhu Lianglin Hu FedML DD AI4CE 47 0 0 05 May 2025
Towards Unbiased Federated Graph Learning: Label and Topology Perspectives Zhengyu Wu Boyang Pang Xunkai Li Y. X. Zhu Daohan Su Bowen Fan R. Li Guoren Wang Chenghu Zhou FedML 33 0 0 14 Apr 2025
Federated Prototype Graph Learning Zhengyu Wu Xunkai Li Y. X. Zhu R. Li Guoren Wang Chenghu Zhou FedML 36 0 0 13 Apr 2025
Adversarial Curriculum Graph-Free Knowledge Distillation for Graph Neural Networks Yuang Jia Xiaojuan Shan Jun-Xiong Xia Guancheng Wan Y. Zhang Wenke Huang Mang Ye Stan Z. Li 42 0 0 01 Apr 2025
Homophily Heterogeneity Matters in Graph Federated Learning: A Spectrum Sharing and Complementing Perspective Wentao Yu FedML 53 0 0 20 Feb 2025