7 citations · 9 across the 4 of their papers we have counts for
4 papers
NodeImport: Imbalanced Node Classification with Node Importance Assessment
Nan Chen, Zemin Liu, Bryan Hooi +3
In real-world applications, node classification on graphs often faces the challenge of class imbalance, where majority classes dominate training, resulting in biased model performa…
Multi-Label Node Classification with Label Influence Propagation
Yifei Sun, Zemin Liu, Bryan Hooi +4
Graphs are a complex and versatile data structure used across various domains, with possibly multi-label nodes playing a particularly crucial role. Examples include proteins in PPI…
Efficient Densest Flow Queries in Transaction Flow Networks (Complete Version)
Jiaxin Jiang, Yunxiang Zhao, Lyu Xu +4
Transaction flow networks are crucial in detecting illicit activities such as wash trading, credit card fraud, cashback arbitrage fraud, and money laundering. \revise{Our collabora…
Partitioning Message Passing for Graph Fraud Detection
Wei Zhuo, Zemin Liu, Bryan Hooi +4
Label imbalance and homophily-heterophily mixture are the fundamental problems encountered when applying Graph Neural Networks (GNNs) to Graph Fraud Detection (GFD) tasks. Existing…