报告时间：2020年8月16日（周日）上午9点（北京时间）开始
报告地点：腾讯会议在线报告
会议链接：//meeting.tencent.com/s/Mhl4tXRCarNc
会议 ID：590 848 008
系列课程讲座题目5：Introduction to Bayesian Statistics and Statistical Learning
课程讲授人：Xiao Wang（美国普渡大学 教授）
报告摘要： Statistics and machine learning have played an important role in modern data analysis and artificial intelligence. This series of lectures will mainly focus on two important topics in statistics: Bayesian Statistics and Statistical Learning. For Bayesian Statistics, I will first present a general framework on Bayesian inference. Then, I will discuss the sampling techniques using Markov Chain Monte Carlo (MCMC). Specific methods include rejection sampling, importance sampling, the Hastings-Metropolis algorithm, and simulated annealing. For Statistical Learning, I will start from the important applications, which are solved by modern learning methods. Then, I will discuss the problems of classification and linear regression. I will further talk about nonparametric methods, such as splines, kernel methods, and tree methods.
报告人简要： Xiao Wang，美国普渡大学统计系教授。 Xiao Wang教授于1997年在中国科技大学获理学学士学位，2000年在中国科技大学获理学硕士学位，2005年毕业于美国密西根大学，获统计学博士学位。Xiao Wang教授的研究兴趣为人工智能，机器学习，非参数统计，大数据分析等方面，并作了大量研究工作。在Annals of Statistics，Journal of the American Statistical Association，Biometrika，AAAI，SIAM Journal of Optimization等统计和人工智能顶级期刊上发表了20余篇论文。
