Parallelisation of sparse grids for large scale data analysis
Sparse Grids (SG), due to Zenger, are the basis for efficient high dimensional approximation and have recently been applied successfully to predictive modelling. They are spanned by a collection of simpler function spaces represented by regular grids. The combination technique prescribes how approximations on simple grids can be combined to approximate the high dimensional functions. It can be improved by iterative refinement. Fitting sparse grids admits the exploitation of parallelism at...[Show more]
|Collections||ANU Research Publications|
|Source:||Computational Science - ICCS 2003|
Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.