学术报告报告主题: Quasi-Monte Carlo Methods and Applications
报 告人: 王小群 教授
报告地点：腾讯会议：555-758-6901
交流QQ群：600788949（发布相关参考文献以及本报告会的最新动态信息）
报告时间：
序号 | 北京时间 | 内容 |
Seminar 1&2 | 5月8日（周日） 10:00-10:45；10:55-11:40 | General principles of MC and QMC; measures of uniformity; error bounds and Koksma-Klawka inequality. |
Seminar 3&4 | 5月15日（周日） 10:00-10:45；10:55-11:40 | Principles and methods of the constructions of low discrepancy sequences, including Halton sequence, Sobol sequence, Faure sequence and Niederreiter sequence. |
Seminar 5&6 | 5月22日（周日） 10:00-10:45；10:55-11:40 | Good lattice rules; Korobov construction; randomized QMC methods. |
Seminar 7&8 | 5月29日（周日） 10:00-10:45；10:55-11:40 | The concept of effective dimensions; applications in finance. |
Seminar 9&10 | 6月5日（周日） 10:00-10:45；10:55-11:40 | Discussion on some recent advances and research topics in QMC (with Zhijian He). |
邀请人:何志坚教授
欢迎广大师生前往！
数学学院
2022年5月3日
报告摘要：Quasi-Monte Carlo (QMC) methods are deterministic versions of Monte Carlo (MC) methods. The basic idea of QMC is to use deterministic low discrepancy points to replace the random points in MC. QMC methods can outperform MC methods for many applications, and have been found enormously useful in statistics and computational finance. In this series of seminars, we first give the general background on QMC methods, including the measures of uniformity and the Koksma-Klawka inequality. Then we describe the principles and methods of the constructions of low discrepancy sequences. We also discuss the methods of good lattice rules and randomized QMC. Some examples will be given in computational finance.
报告人简介：王小群，清华大学数学科学系长聘教授、博导，国家级人才；2009年获国家杰出青年科学基金。主要从事金融数学、计算金融学、数据科学和统计计算的研究。王小群教授在运筹学和管理科学的两大国际旗舰刊物Management Science和Operations Research以及在计算科学 的国际著名刊物 SIAM J. Numer. Anal., SIAM J. Sci. Comput., Math. Comp., Numer. Math. 等发表论文数十篇。担任或曾任全国应用统计专业学位研究生教育指导委员会委员，中国工业与应用数学学会秘书长、常务理事，中国运筹学会金融工程和风险管理分会副理事长。