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学术报告公告

Communication-efficient distributed statistical inference on zero-inflated Poisson models

一、报告主题：Communication-efficient distributed statistical inference on zero-inflated Poisson models

二、主 讲 人：柏杨，博士，副教授，博士生导师。

三、报告时间：2025年5月22日下午15:00

四、报告地点：明达楼（办公楼）D2433室

五、报告简介：

Zero-inflated count outcomes are common in many studies, such as counting claim frequency in the insurance industry in which identifying and understanding excessive zeros are of interest. Moreover, with the progress of data collecting and storage techniques, the amount of data is too massive to be stored or processed by a single node or branch. Hence, to develop distributed data analysis is blossoming. In this paper, several communication-efficient distributed zero-inflated Poisson regression algorithms are developed to analyse such kind of large-scale zero-inflated data. Both asymptotic properties of the proposed estimators and algorithm complexities are well studied and conducted. Various simulation studies demonstrate that our proposed method and algorithm work well and efficiently. Finally, in the case study, we apply our proposed algorithms to car insurance data from Kaggle.

主办：数理学院        

2025年5月21日