报告题目：Review of Distributed Statistical Inference（分布式统计分析）

报告时间：2021年6月25日下午1点30分

报告形式：腾讯会议

会议链接：https://meeting.tencent.com/s/uunq7ey0KRtV

会议 ID：753 516 304

主办单位：科研处/437必赢会员中心网页版

主讲人：张日权

张日权简介：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。

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.