报告人：张日权，华东师范大学统计学院院长、博士生导师
时 间：2021年5月13日15:00 —
地 点：燕山校区1号教学楼1502会议室
摘 要：The rapid emergence of massive datasets in various fields poses a serious challenge to traditional statistical methods. Meanwhile, it provides opportunities for researchers to develop novel algorithms. Inspired by the idea of divide-and-conquer, various distributed frameworks for statistical estimation and inference have been proposed. They were developed to deal with large-scale statistical optimization problems. This report aims to provide a comprehensive review for related literature. It includes parametric models, nonparametric models, and other frequently used models. Their key ideas and theoretical properties are summarized. The trade-off between communication cost and estimate precision together with other concerns are discussed.
主讲人简介：张日权，华东师范大学统计学院院长，教育部统计与数据科学前沿理论及应用重点实验室主任，《应用概率统计》期刊常务副主编，中国现场统计研究会大数据统计分会 理事长，中国商业统计学会数据科学与商业智能分会副理事长，上海统计学会副会长。主要研究方向：大数据统计，金融统计，非/半参数统计，超/高维数据分析，函数型数据分析、统计机器学习。
科研处 统计学院（大数据与指数研究院）
