SC²S Colloquium - December 13, 2012

Date:	November 28, 2012
Room:	02.07.023
Time:	3 pm, s.t.

Florian Zacherl: Using pre-computed matrices in a density-based classification method with sparse grids

Classification of huge data sets is a process that requires long computation times, especially with high-dimensional data. A way to reduce this is to use function approximation on a sparse grid. Still this might not be enough for big data sets. This IDP examines a further optimization by using a density-based approach that allows to do a relevant part of the work in advance without the actual data. More precisely, the solving of a linear system of equations is simplified by pre-computing, decomposing and storing the left hand side matrix of the system.