数学与统计学院学术报告[2021] 009号

(高水平大学建设系列报告509号)

报告题目: Latent Factor Model and Its Applications to Recommender System, Network Embedding and Beyond

报告人：王军辉　　教授  （ 香港城市大学）

报告时间：3月11日16:00-17:00

报告地点：汇星楼514　　　　　　　　　　　　　 　　

报告内容：

Latent factor model has a long history in statistics and can be dated back to early 1900s. In this talk, we will talk about a number of modern applications of latent factor model, including recommender system, network embedding, as well as crowdsourcing. Interestingly, these applications are often referred to as the unstructured data, but all lead to similar matrix

type of data structure, and thus are particularly suitable for latent factor model. We will develop some exible yet powerful modeling strategies based on latent factor model, to tackle the cold-start issue in recommender system and community detection in networks. The developed models are supported by a variety of real applications as well as their asymptotic properties.

报告人简历：

王军辉教授现为香港城市大学数据科学学院教授。他本科毕业于北京大学，研究生毕业于美国明尼苏达大学并获得统计学博士学位。在加入香港城市大学之前，王军辉教授曾任教于美国哥伦比亚大学和伊利诺伊大学芝加哥分校。他的研究方向包括统计机器学习及其在生物医学，经济，金融，和信息技术上的应用。他的研究成果广泛发表于Journal of American Statistical Association, Biometrika, 和Journal of Machine Learning Research等统计及机器学习的顶级期刊，并担任Statistica Sinica, Annals of the Institute of Statistical Mathematics和Statistics and its interface等期刊的副主编。

欢迎感兴趣的师生参加！

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                                              2021年3月8日