澳门新葡8455最新网站,www.8455.com,新葡京最新官网

当前位置: 澳门新葡8455最新网站 > 学术活动 > 正文
Identifying Conditional Dependence Structure when Data are Multiple Curves
澳门新葡8455最新网站:2016年12月09日 14:21 点击数:

报告人:郭绍俊

报告地点:澳门新葡8455最新网站四楼报告厅

报告澳门新葡8455最新网站:2016年12月12日星期一10:30-11:30

邀请人:

报告摘要:

Graphical models have attracted increasing attention in recent years, especially in settings involving high dimensional data. In particular Gaussian graphical models are used to model the conditional dependence structure among multiple Gaussian random variables. As a result of its computational e_ciency the graphical lasso (glasso) has become one of the most popular approaches for fitting high dimensional graphical models. In this article we extend the graphical models concept to model the conditional dependence structure among p random functions. In this setting, not only is p large, but each function is itself a high dimensional object, posing an additional level of statistical and computational complexity. We develop an extension of the glasso criterion (fglasso), which estimates the functional graphical model by imposing a block sparsity constraint on the precision matrix, via a group lasso penalty. The fglasso criterion can be optimized using an e_cient block coordinate descent algorithm. We establish the concentration inequalities of the estimates, which guarantee the desirable graph support recovery property, i.e. with probability tending to one, the fglasso will correctly identify the true conditional dependence structure. Finally we show that the fglasso significantly outperforms possible competing methods through both simulations and an analysis of a real world EEG data set comparing alcoholic and non-alcoholic patients.

主讲人概况:

郭绍俊,2003年毕业于山东师范大学,2008年获得中国科新葡京最新官网数学与系统科学研究院理学博士学位。博士毕业后留中国科新葡京最新官网数学与系统科学研究院工作,助理研究员,任期至2016年。工作期间,于2009年-2010年赴美国普林斯顿大学运筹与金融工程系博士后研究,做高维数据分析方面的研究工作,并于2014-2016年在英国伦敦经济新葡京最新官网统计系做访问博士后研究,做大维澳门新葡8455最新网站序列建模方面的研究。 现为中国人民大学统计与大数据研究院副教授。目前主要研究方向有:高维统计学习;非参数及半参数统计建模;大维统计计算;生存分析及函数型数据分析等。

Copyright ©版权所有:澳门新葡8455最新网站

地址:吉林省长春市人民大街5268号|邮编:130024|电话:0431-85099589|传真:0431-85098237


XML 地图 | Sitemap 地图