报告题目：Quasi-interpolation for high-dimensional function approximation

报告人：高文武 教授 (安徽大学)

报告时间：2022年4月24日 20:00-21:00

报告地点：腾讯会议 ID: 125-951-493

主持人：赵微

报告摘要：Quasi-interpolation has been a useful tool for approximation. In this talk, I shall introduce some recent results of our team on constructing quasi-interpolation schemes for approximating high- dimensional function and provide some applications of our quasi- interpolation schemes. In particular, we shall focus on how to construct radial kernel and aniostropic tensor-product kernel such that the resulting quasi-interpolation schemes can break the curse of dimensionality. In addition, we shall study some properties of quasi-interpolation and its applications in constructing structure- preserving schemes for numerical solutions of PDEs.

简介：高文武教授，安徽大学统计学系博士生导师，统计学博士点负责人、应用统计专硕硕士点负责人。研究工作主要聚焦在统计学与数据科学领域交叉方向的核心基础算法的构造理论及其应用如概率数值逼近、统计学习、无网格微分方程数值解等，先后获得国家自然科学基金青年项目、面上项目的资助，在SIAM J. Numer. Anal., SIAM J. Sci. Comput., Adv. Comput. Math., Appl. Math. Model., Numer. Algor., 等期刊发表SCI论文20余篇。