We study the problem of community detection in multi-layer networks, where pairs of nodes can be related in multiple modalities. We introduce a general framework, i.e., mixture multi-layer stochastic block model (MMSBM), which includes many earlier models as special cases. We propose a tensor-based algorithm (TWIST) to reveal both global/local memberships of nodes, and memberships of layers. We show that the TWIST procedure can accurately detect the communities with small misclassification error as the number of nodes and/or number of layers increases. Numerical studies confirm our theoretical findings. To our best knowledge, this is the first systematic study on the mixture multi-layer networks using tensor decomposition. The method is applied to two real datasets: worldwide trading networks and malaria parasite genes networks, yielding new and interesting findings.

5月3日
4:30pm - 5:30pm
地点
https://hkust.zoom.us/j/99057265284 (Passcode: 123456)
讲者/表演者
Mr. Zhongyuan LYU
主办单位
Department of Mathematics
联系方法
付款详情
对象
Alumni, Faculty and staff, PG students, UG students
语言
英语
其他活动
4月26日
研讨会, 演讲, 讲座
IAS / School of Science Joint Lecture - Molecular Basis of Wnt Biogenesis, Secretion and Ligand Specific Signaling
Abstract Wnt signaling is essential to regulate embryonic development and adult tissue homeostasis. Aberrant Wnt signaling is associated with cancers. The ER-resident membrane-bound O-acyltransfera...
4月18日
研讨会, 演讲, 讲座
IAS / School of Science Joint Lecture - Understanding the Roles of Transposable Elements in the Human Genome
Abstract Transposable elements (TEs) have expanded the binding repertoire of many transcription factors and, through this process, have been co-opted in different transcriptional networks. In this ...