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Review of Distributed Statistical Inference

来源: 发布时间: 2022-06-07 点击量:
  • 主持人: 陈夏教授
  • 讲座人: 张日权教授
  • 讲座日期: 2022年6月10日
  • 讲座时间: 15:00
  • 地点: 腾讯会议(ID:160 331 424)

讲座人简介:张日权,华东师范大学统计学院院长,教授,博士生导师。担任教育部统计与数据科学前沿理论及应用重点实验室主任,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,《应用概率统计》期刊常务副主编。主持多项国家自然科学基金、教育部博士点基金、国家统计局重点项目等研究项目20多项;发表论文170余篇,SCI收录论文130余篇,出版专著2部,教材2部。先后获得上海市育才奖,上海市自然科学奖三等奖,上海市教学成果一等奖。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。

讲座简介: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.

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