学术报告-江颖

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2018-10-12 08:59:00

学术报告

题      目:高维稀疏网格逼近及其在积分方程、随机微分方程中的应用


报  告  人:江颖     (邀请人: 叶颀)

                                 中山大学


时      间:2018-10-12 11:00--12:00

地      点:学院401

报告人简介:

        中山大学数据科学与计算机学院副教授、博士生导师,数据科学系副系主任,广东省计算科学重点实验室主任助理。主要从事高维数据稀疏表示、积分方程快速算法等方面的研究,在Siam. Numer. Anal.、Math. Comp.、J. Sci. Comput.、JCAM等计算数学重要期刊上发表SCI论文10余篇。主持国家自然科学基金2项、广州市重点项目1项。



摘      要:

       This talk is about a kind of high-dimension approximation techniques, called sparse grids,which are widely used in solving partial differential equations, integral equations,designing high-dimension quadrature formula, data mining, etc. The approximation schemes on sparse grids achieve quasi-linear computational cost when the schemes on full grids suffer from the ``curse of dimensionality'', since the computational complexity increases exponentially as the dimension grows. At same time, the approximation
schemes on sparse grids enjoy the optimal approximation order as the schemes on full grids do.