Garcke, Jochen; Hegland, Markus; Nielsen, Ole
Sparse grids 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 sparse grid combination technique prescribes how approximations on a collection of anisotropic grids can be combined to approximate high dimensional functions. In this paper we study the parallelisation of fitting data onto a sparse grid. The computation can be...[Show more]
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