统计学系系列讲座之373期

时   间:2021年6月4日(星期五)15:30-16:30

地   点:史带楼302室

主持人:张新生  教授 复旦大学管理学院统计学系

主   题:Learning Mixed Latent Tree Models

主讲人:郭建华 教授  东北师范大学

简   介:郭建华,东北师范大学副校长,教授,博士生导师。国务院学位委员会学科评议组统计学科召集人,国家杰出青年科学基金获得者,教育部“**学者奖励计划”特聘教授,“新世纪百千万人才工程”国家级人选,国务院政府特殊津贴获得者,IMS Fellow, ISI Elected Member,国家社会科学基金学科规划评议组成员,国家自然科学基金会评专家,著名期刊《JASA》、《统计研究》等的编委。

摘   要:

Latent structural learning has attracted more attention in recent years. But most related works only focuses on pure continuous or pure discrete data. In this talk, we will consider mixed latent tree models for mixed data mining. We address the latent structural learning and parameter estimation for those mixed models. For structural learning, we propose a consistent bottom-up algorithm, and give a finite sample bound guarantee for the exact structural recovery. For parameter estimation, we suggest a moment estimator by exploiting matrix decomposition, and prove asymptotic normality of the estimator. Experiments on the simulated and real data support that our method is valid for mining the hierarchical structure and latent information.

 

统计学系 

2021-6-2