4 papers
Is Fixing Schema Graphs Necessary? Full-Resolution Graph Structure Learning for Relational Deep Learning
Yi Huang, Qingyun Sun, Jia Li +2
Relational prediction tasks are fundamental in many real-world applications, where data are naturally stored in relational databases (RDBs). Relational Deep Learning (RDL) addresse…
Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning
Yi Huang, Qingyun Sun, Yisen Gao +3
The Information Bottleneck (IB) principle facilitates effective representation learning by preserving label-relevant information while compressing irrelevant information. However,…
Unifying Deductive and Abductive Reasoning in Knowledge Graphs with Masked Diffusion Model
Yisen Gao, Jiaxin Bai, Yi Huang +3
Deductive and abductive reasoning are two critical paradigms for analyzing knowledge graphs, enabling applications from financial query answering to scientific discovery. Deductive…
No Data? No Problem: Synthesizing Security Graphs for Better Intrusion Detection
Yi Huang, Shaofei Li, Yao Guo +3
Provenance graph analysis plays a vital role in intrusion detection, particularly against Advanced Persistent Threats (APTs), by exposing complex attack patterns. While recent syst…