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報告題目：Sequential data integration under dataset shift

主講人：盛贏 助理研究員（中國科學院數學與系統科學研究院）

時間：2024年12月13日（周五）10:00 a.m.

地點：北院卓遠樓305會議室

主辦單位：統計與數學學院

摘要：With the rapidly increasing availability of large-scale and high-velocity streaming data, efficient algorithms that can process data in batches without requiring expensive storage and computation resources have drawn considerable attention. An emerging challenge in developing efficient batch processing techniques is dataset shift, where the joint distribution of the collected data varies across batches. If not recognized and addressed properly, dataset shift often leads to erroneous statistical inferences when integrating data from different batches. In this paper, two shift-adjusted estimation procedures are developed for updated estimation of the parameter in the presence of dataset shift. Under prior probability shift, we can obtain parameter estimation and assess the degree of dataset shift simultaneously. We study the asymptotic properties of the proposed estimators and evaluate their performance in numerical studies. The proposed methodologies are illustrated with an analysis of the Ford GoBike docked bike-sharing data. This is a joint work with Jing Qin and Chiung-Yu Huang.

主講人簡介：

中國科學院數學與系統科學研究院助理研究員。2018年在中國科學院數學與系統科學研究院獲得博士學位，隨后在加州大學舊金山分校從事博士后研究工作。主要研究方向為整合分析、可更新估計、生存分析等，在Biometrics、Technometrics、Statistics in Medicine、Statistica Sinica 等期刊發表學術論文10余篇。主持國家自然科學基金青年項目。