most citedMultitask Active Learning for Graph Anomaly Detection

2 citations · 2 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2024

Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement

Wenjing Chang, Kay Liu, Philip S. Yu +1

Graph anomaly detection (GAD) is increasingly crucial in various applications, ranging from financial fraud detection to fake news detection. However, current GAD methods largely o…

cs.LG2024★ 2 cited

Multitask Active Learning for Graph Anomaly Detection

Wenjing Chang, Kay Liu, Kaize Ding +2

In the web era, graph machine learning has been widely used on ubiquitous graph-structured data. As a pivotal component for bolstering web security and enhancing the robustness of…