報告題目：Distributed inference for two-sample U-statistics in massive data analysis
報 告 人：劉妍岩 教授 武漢大學數學與統計學院
報告時間：2023年5月10日 10：00-11：00
報告地點：騰訊會議 ID：914918095
校内聯系人：王培潔 wangpeijie@jlu.edu.cn
報告摘要：This paper considers distributed inference for two-sample U-statistics under the massive data setting. In order to reduce the computational complexity, this paper proposes distributed two-sample U-statistics and block-wise linear two sample U-statistics. The block-wise linear two-sample U-statistic, which requires less communication cost, is more computationally efficient especially when the data are stored in different locations. The asymptotic properties of both types of distributed two-sample U-statistics are established. In addition, this paper proposes bootstrap algorithms to approximate the distributions of distributed two-sample U-statistics and block-wise linear two-sample U-statistics for both non-degenerate and degenerate cases. The distributed weighted bootstrap for the distributed two-sample U-statistic is new in the literature. The proposed bootstrap procedures are computationally efficient and are suitable for distributed computing platforms with theoretical guarantees. Extensive numerical studies illustrate that the proposed distributed approaches are feasible and effective.
報告人簡介：劉妍岩，武漢大學數學與統計學院教授，博士生導師。2001年獲武漢大學理學博士學位。主要研究方向為生存分析、半參數統計推斷、複雜高維數據模型結構選擇以及大數據統計分析技術等。曾到美國北卡來羅納大學教堂山分校、加拿大Simon-Fraser大學、香港理工大學、香港中文大學、德國Greifswald大學等學校短期訪問和工作。主持完成國家自然科學基金以及教育部基金項目6項，目前主持國家自然科學基金面上項目一項。在統計學期刊 Journal of Machine Learning Research, Biometrics, Biostatistics, Genetics，Lifetime Data Analysis等期刊發表SCI研究論文六十餘篇。目前擔任statistical papers 副主編，以及中國現場統計學會第十一屆理事會常務理事、中國數學會女專家工作委員會委員、全國應用統計教指委委員（2022-）。
