11 search results - page 1 / 3 » Sparse Grids, Adaptivity, and Symmetry |
COMPUTING
2006
13 years 4 months ago
2006
Sparse grid methods represent a powerful and efficient technique for the representation and approximation of functions and particularly the solutions of partial differential equat...
ICCS
2007
Springer
13 years 8 months ago
2007
Springer
Common techniques tackling the task of classification in data mining employ ansatz functions associated to training data points to fit the data as well as possible. Instead, the fe...
IPPS
1999
IEEE
13 years 9 months ago
1999
IEEE
Many numerical solutions of large scale simulation models require finer discretizations in some regions of the computational grid. When this region is not known in advance, adapti...
NECO
2008
13 years 4 months ago
2008
Current models for the learning of feature detectors work on two time scales: on a fast time scale the internal neurons' activations adapt to the current stimulus; on a slow ...
AAECC
2007
Springer
13 years 4 months ago
2007
Springer
We present a simulation-based performance model to analyze a parallel sparse LU factorization algorithm on modern cached-based, high-end parallel architectures. We consider supern...