Name
Abstract | ||
|---|---|---|
We consider the multiple point evaluation problem for an n-dimensional space of functions [驴驴驴1,1[ d 驴驴 spanned by d-variate basis functions that are the restrictions of simple (say linear) functions to tensor product domains. For arbitrary evaluation points this task is faced in the context of (semi-)Lagrangian schemes using adaptive sparse tensor approximation spaces for boundary value problems in moderately high dimensions. We devise a fast algorithm for performing m驴驴驴n point evaluations of a function in this space with computational cost O(mlog d n). We resort to nested segment tree data structures built in a preprocessing stage with an asymptotic effort of O(nlog d驴驴驴1 n). |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/s11075-012-9624-4 | Numerical Algorithms |
Keywords | Field | DocType |
(Multilevel) segment tree,Adaptive sparse tensor product approximation | Tensor product,Data structure,Discrete mathematics,Boundary value problem,Mathematical optimization,Lagrangian,Tensor,Mathematical analysis,Preprocessor,Basis function,Segment tree,Mathematics | Journal |
Volume | Issue | ISSN |
63 | 2 | 1017-1398 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| R. Hiptmair | 1 | 199 | 38.97 |
| G. Phillips | 2 | 0 | 0.34 |
| G. Sinha | 3 | 0 | 0.34 |