Please note: This PhD seminar will take place in DC 2306 and online.
Jingbang Chen, PhD candidate
David R. Cheriton School of Computer Science
Supervisor: Professor Lap Chi Lau
We will be discussing a joint work with Qiuyang Mang, Hangrui Zhou, Richard Peng, Yu Gao, Chenhao Ma, which is accepted by KDD2024. Signed networks, characterized by edges labeled as either positive or negative, offer nuanced insights into interaction dynamics beyond the capabilities of unsigned graphs. Central to this is the task of identifying the maximum balanced subgraph, crucial for applications like polarized community detection in social networks and portfolio analysis in finance. Traditional models, however, are limited by an assumption of perfect partitioning, which fails to mirror the complexities of real-world data. Addressing this gap, we introduce an innovative generalized balanced subgraph model that incorporates tolerance for irregularities. Our proposed region-based heuristic algorithm, tailored for this NP-hard problem, strikes a balance between low time complexity and high-quality outcomes. Comparative experiments validate its superior performance against leading solutions, delivering enhanced effectiveness (notably larger subgraph sizes) and efficiency (achieving up to 100x speedup) in both traditional and generalized contexts.
To attend this PhD seminar in person, please go to DC 2306. You can also attend virtually via Zoom.