嘉宾简介
李雪曈，北京大学光华管理学院商务统计与经济计量系在读博士生，师从王汉生教授。主要研究方向包括非均衡数据分析，网络结构数据分析，分布式计算等。研究论文发表在Electronic Journal of Statistics，Statistica Sinica期刊上。
报告摘要
Large-scale rare events data are commonly encountered in practice. To tackle the massive rare events data, we propose a novel distributed estimation method for logistic regression in a distributed system. For a distributed framework, we face the following two challenges. The first challenge is how to distribute the data. In this regard, two different distribution strategies (i.e., the RANDOM strategy and the COPY strategy) are investigated. The second challenge is how to select an appropriate type of objective function so that the best asymptotic efficiency can be achieved. Then, the under-sampled (US) and inverse probability weighted (IPW) types of objective functions are considered. Our results suggest that the COPY strategy together with the IPW objective function is the best solution for distributed logistic regression with rare events. The finite sample performance of the distributed methods is demonstrated by simulation studies and a real-world Sweden Traffic Sign dataset.
直播报告时间：2023年6月16日
