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Noisy nonlinear information and entropy numbers
David Krieg, Erich Novak, Leszek Plaskota +1
It is impossible to recover a vector from with less than linear measurements, even if the measurements are chosen adaptively. Recently, it has been shown that on…
math.NA2025
Sparse grids vs. random points for high-dimensional polynomial approximation
Jakob Eggl, Elias Mindlberger, Mario Ullrich
We study polynomial approximation on a -cube, where is large, and compare interpolation on sparse grids, aka Smolyak's algorithm (SA), with a simple least squares method bas…