Polynomial Interpolation in Several Variables: Lattices, Differences, and Ideals

By Tomas Sauer. 2006

47 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computational Theory and Mathematics, Signal Processing

View Paper: https://www.semanticscholar.org/paper/954769234da453326e97ac88b6c7f9ea8d0e625c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Mechanics

1. Michael Kohler
2. Benedikt Bauer

In Computational Theory and Mathematics

1. Michael Kohler
2. Benedikt Bauer

In Signal Processing

1. Michael Kohler
2. Benedikt Bauer

Citations in the corpus

• On deep learning as a remedy for the curse of dimensionality in nonparametric regression (2019, methodology): “Then the polynomial Proposition 4 in Sauer (2006) implies that the condition (22) has the only solution p = 0 in P N for Lebesgue almost all α 1 , . . . α K ∈ R d +1 , which in turn implies (21).”