Approximation of Functions on Manifolds in High Dimension from Noisy Scattered Data

In this paper, we consider the fundamental problem of approximation of functions on a low-dimensional manifold embedded in a high-dimensional space, with noise affecting both in the data and values of the functions. Due to the curse of dimensionality, as well as to the presence of noise, the classic...

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Hauptverfasser:	Faigenbaum-Golovin, Shira, Levin, David
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Numerical Analysis Mathematics - Numerical Analysis
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