The Sparse Grid Method

author: Jochen Garcke, Institute for Mathematics, TU Berlin
published: Feb. 25, 2007,   recorded: February 2006,   views: 1703
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Delicious Bibliography

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 54:01
!NOW PLAYING
Watch Part 2
Part 2 31:02
!NOW PLAYING

Description

The sparse grid method is a special discretization technique, which allows to cope with the curse of dimensionality to some extent. It is based on a hierarchical basis and a sparse tensor product decompositon. Sparse grids have been successfully used to solve partial differential equations in the past and, more recently, have been shown to be competitive for learning problems as well. The lecture will provide a general introduction to the major properties of sparse grids and present the sparse grid combination technique for classification and regression.

See Also:

Download slides icon Download slides: mlss06au_garcke_sgm.pdf (1.2┬áMB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: