开放课件详细信息
Approximating Functions in High Dimensions
授课人:Albert Cohen
机构:Pacific Institute for the Mathematical Sciences(PIMS)
关键词: Scientific;    Mathematics;    Functional Analysis;   
加拿大|英语
【 摘 要 】
This talk will discuss mathematical problems which are challenged by the fact they involve functions of a very large number of variables. Such problems arise naturally in learning theory, partial differential equations or numerical models depending on parametric or stochastic variables. They typically result in numerical difficulties due to the so-called ''curse of dimensionality''. We shall explain how these difficulties may be handled in various contexts, based on two important concepts: (i) variable reduction and (ii) sparse approximation.
【 授权许可】

CC BY-NC-ND   
Except where explicitly noted elsewhere, the works on this site are licensed under a Creative Commons License: CC BY-NC-ND

附件列表
Files Size Format View
RO201805250000241SX.mp4 KB MovingImage download
  文献评价指标  
  下载次数:5次 浏览次数:18次