报告题目:Statistical inference for mean-field queueing models
报告人：赵以强 教授（Carleton University）
时间：5月5日下午3点
地点：长望楼报告厅
主持人：张建伟 教授
报告摘要：
Last year, in 2022, to celebrate the publication of the 100th volume, Queueing Systems published a special issue containing 100 Views on Queues. I presented my suggestions of research in the area of statistical inference for mean-filed queueing models.
The idea of mean-field approximations originated from works by Curie (1895) and Weiss (1907) in the area of statistical physics. Since then, it has been developed into a very important approximation tool for describing a large number of interacting particles systems (IPS) for many important applications in various fields, including queueing theory.
Applications of mean-field approximations to queueing systems go back to Dobrushin and Sukhov (1976). Research on statistical inference for mean-field models started only in recent years due to difficulties as stated in Della Maestra and Hoffmann (2021): (1) the required fine probabilistic tools were still in full development; and (2) the motivation for statistical inference is not obvious.
So far, most of statistical inference studies on mean-field models are for continuous state systems, and the study on discrete-state queueing models has not yet started. In this talk, we demonstrate by two queueing models how to do statistical inference for queueing models.
数学与统计学院
2023年5月4日
