Parallelisation of sparse grids for large scale data analysis
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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