主题：Two-way Node Popularity Model for Directed and Bipartite Networks
主讲人：王江洲 深圳大学
主持人：朱海斌 暨南大学
时间：2025年12月1日（周一）下午16:30-17:30
地点：暨南大学石牌校区经济学院大楼（中惠楼）323室
摘要
There has been extensive research on community detection in directed and bipartite networks. However, these studies often fail to consider the popularity of nodes in different communities, which is a common phenomenon in real-world networks. To address this issue, we propose a new probabilistic framework called the Two-Way Node Popularity Model (TNPM). The TNPM also accommodates edges from different distributions within a general sub-Gaussian family. We introduce the Delete-One-Method (DOM) for model fitting and community structure identification, and provide a comprehensive theoretical analysis with novel technical skills dealing with sub-Gaussian generalization. Additionally, we propose the Two-Stage Divided Cosine Algorithm (TSDC) to handle large-scale networks more efficiently. Our proposed methods offer multi-folded advantages in terms of estimation accuracy and computational efficiency, as demonstrated through extensive numerical studies. We apply our methods to two real-world applications, uncovering interesting findings.
主讲人简介
王江洲，深圳大学数学科学学院，统计与数据科学系助理教授。主要研究方向：大规模网络数据的统计分析、大规模相依数据的多重检验、机器学习和深度学习等与统计学的交叉。目前在统计学领域期刊发表SCI论文十余篇，其中包括：JASA、JCGS、JMVA、CSDA、Computational Statistics 和 Stat等国际期刊。主持科研项目：国家自然科学基金青年项目1项、广东省自然科学基金面上项目1项、中国博士后科学基金面上项目和特别资助（站中）项目各1项、参与面上项目1项。入选深圳市“鹏城孔雀计划”特聘岗位C岗。曾多次受邀在ICSA等国际会议上做报告，并担任JMLR, AOAS, Sinica, JCGS, CSDA和SII等期刊的审稿人。
欢迎感兴趣的师生参加！
校对|朱海斌
责编| 彭毅
初审| 姜云卢
终审发布| 何凌云
（来源：暨南大学经济学院微信公众号）
