主讲人：Julius Vainora，剑桥大学经济系助理教授, 博士生导师。他于2020年获得马德里卡洛斯三世大学的经济学博士学位。研究方向为机器学习、计量经济学，以及网络科学。他对于经济网络的统计推断研究取得的成果引起学术界的广泛关注。

主办单位：南开大学金融学院数字金融研究所

主讲时间：2022年3月21日、22日晚7：00

内容摘要

机器学习理论与算法是剑桥大学经济系的博士生课程。本课程专为希望对机器学模型、算法和理论有所基本理解的学生和研究者设计，广受剑桥大学师生好评。讲座将在原有课程的基础上稍作简化，并以应用为导向, 以便不同年级的同学参与。在两个两小时的讲座中，Julius Vainora博士首先将对机器学习做一个入门指南，接着他将着重于两个话题：（1）神经网络；（2）树模型与集成学习。

Dr. Julius Vainora is an assistant professor and Ph.D.advisor at the faculty of economics, University of Cambridge. He received his Ph.D. from the Universidad Carlos III de Madrid in 2020. His fields of interest are machine learning, econometrics, and networks. His research in network dependence and statistical inference attracts wide attention in the community.

Machine learning theory and algorithms is a Ph.D. level course at the University of Cambridge. The course is designed for students and researchers who wish to have a fundamental understanding of machine learning models, algorithms, and theoretical properties. And the course is very well received by the students and the faculty. The lectures will be slightly simplified for it to be friendly for a broad audience. And it will be application-oriented. In the two two-hour lectures, Dr. Julius Vainora will first give a broad introduction to machine learning. Then, he will focus on two topics: (1) neural networks; (2) tree-based algorithms and ensemble learning.