4 papers
MM-OpenFGL: A Comprehensive Benchmark for Multimodal Federated Graph Learning
Xunkai Li, Yuming Ai, Yinlin Zhu +7
Multimodal-attributed graphs (MMAGs) provide a unified framework for modeling complex relational data by integrating heterogeneous modalities with graph structures. While centraliz…
Federated Graph Unlearning
Yuming Ai, Xunkai Li, Jiaqi Chao +5
The demand for data privacy has led to the development of frameworks like Federated Graph Learning (FGL), which facilitate decentralized model training. However, a significant oper…
A Comprehensive Data-centric Overview of Federated Graph Learning
Zhengyu Wu, Xunkai Li, Yinlin Zhu +8
In the era of big data applications, Federated Graph Learning (FGL) has emerged as a prominent solution that reconcile the tradeoff between optimizing the collective intelligence b…
OpenGU: A Comprehensive Benchmark for Graph Unlearning
Bowen Fan, Yuming Ai, Xunkai Li +3
Graph Machine Learning is essential for understanding and analyzing relational data. However, privacy-sensitive applications demand the ability to efficiently remove sensitive info…