报告主题：Matrix differential calculus with applications in statistical learning
时间：2025年5月27日10:45-11:30

地点：上川路校区一教218 

报告人：刘双喆

报告内容简介：

Matrix differential calculus plays a very important role in statistical learning and data science. In this talk, we start with a big picture of mathematics (including calculus, linear algebra, probability, and statistics), useful to statistical learning. We then pay particular attention to matrix differential calculus and its applications to the multivariate linear model, including efficiency comparisons, sensitivity analysis, and statistical diagnostics. 

主讲人简介：

Shuangzhe Liu currently serves as the leader of the Data Science Group within the Faculty of Science and Technology at the University of Canberra, Australia. He obtained his Ph.D. in Econometrics from the Tinbergen Institute, University of Amsterdam, the Netherlands, specializing in matrix differential calculus, multivariate analysis, and statistical learning. His extensive expertise is evidenced by his numerous publications in prestigious journals in the fields of econometrics, mathematics, statistics, and related areas. Additionally, he has co-authored a comprehensive book on time series analysis using SAS Enterprise Guide. Demonstrating a strong commitment to advancing statistical knowledge, Shuangzhe actively contributes to the field as an associate editor for multiple statistical journals and holds an editor position at Statistical Papers.