报告人:高文武 教授(安徽大学)
时 间:2021年10月12日16:00开始
地 点:数统院307室
报告摘要: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 schems 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.
报告人简介:高文武,安徽大学统计学系教授、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。复旦大学应用数学专业博士,上海宝钢研究院与复旦大学管理学院统计系博士后,美国科罗拉多矿业大学应用数学与统计学访问副教授。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、不确定量化、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 Journal on Numerical Analysis, SIAM Journal on Scientific Computing, Advances in Computational Mathematics, Numerical Algorithms, Applied Mathematical Modelling, Applied Numerical Mathematics, Journal of Computational and Applied Mathematics国际知名期刊上发表多篇学术论文。