题目：A Refined Lindeberg Principle and Its Applications
报告人：陈鹏（南京航空航天大学）
时间：5月26日（星期五），15:30-17:00
地点：Zoom会议，会议号：876 0592 8254，会议密码: 2023
摘要：We view the classical Lindeberg principle in a homogeneous Markov proc-ess setting to establish a probability approximation framework by the associatedIto's formula and Markov operator. As applications, we study the error bounds ofthe following three approximations: multivariate normal approximation, approx1.mating a family of online stochastic gradient descents (SGDs) by a stochasticdifferential equation (SDE) driven by multiplicative Brownian motion. andEuler-Maruyama (EM) discretization for SDEs driven by alpha-stable process.Furthermore, we extend the above approximation framework to the inhomo-geneous case and consider the variable-step E-M approximations of regime-switching jump diffusion processes. This talk is based on the joint works with OM. Shao. Z.G.Su C. Deng and L.Xu .
报告人简介：陈鹏，南京航空航天大学数学学院讲师。2021年于澳门大学科技学院获得概率论与数理统计博士学位，研究方向为概率极限理论，随机过程，随机算法，在Annals of Applied Probability,Applied Mathematics and Optimization Journal of Theoretical Probability, Electronic Joural of Statistics等杂志发表多篇文章，主持一项江苏省自然科学基金青年基金项目。
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