SCCS Colloquium - May 8, 2019

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Date: May 8, 2019
Room: 02.07.023
Time: 15:00 - 16:00

Nico Rösel: Combigrid Based Dimensional Adaptivity for Sparse Grid Density Estimation and Classification

This is a Bachelor's thesis submission talk. Nico is advised by Kilian Röhner and Michael Obersteiner.

In the frame of this thesis the sparse grid combination technique was used to expand the density estimation based approach to classification in the SG++ framework. Thanks to the independence of the component grids, it was possible to implement much faster dimensional adaptive refinements. While the old implementation had to refit the whole grid after each refinement step, now just the additionally added components have to be fitted. The thesis contains the theoretical background, a description, and an evaluation of the implementation.

Keywords: sparse grids, combination technique, classification, density estimation, SG++, SpACE

Language: German


We are looking for a second talk! Please use the Colloquium registration form.

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