报告题目：Modeling complex time series with tensor techniques
报 告 人：李国栋 香港大学
报告时间：2023年6月13日(周二)，16:30-18:00
腾讯会议ID：929 2139 6317
内容摘要
The tensor, as an extension of matrices, has recently gained significant attention from econometricians and statisticians, and the literature has witnessed two types of its applications. Firstly, the involvement of tensors can facilitate the development of new inference tools, which are impossible under the framework of matrices alone. Secondly, many big data come in the form of tensors. This talk will introduce several of my research studies on high-dimensional time series modeling using tensors, and I will also present two inference tools for tensor-valued time series.
主讲人简介
李国栋，现任香港大学统计精算系教授。本科和硕士毕业于北京大学数学学院，2007年于香港大学统计精算系获得统计学博士，随后在南洋理工大学任助理教授。主要研究方向包括计量经济，时间序列分析，分位数回归，高维统计数据分析和机器学习。李教授目前发表学术论文60余篇，其中20余篇发表在Journal of Econometrics, Econometric Theory和Journal of Business and Economic Statistics等计量经济学的顶级期刊，以及统计学4大顶级期刊和机器学习的3大顶级会议上。
