Sampling in Function Approximation

Sampling is crucial for the stability and accuracy of various global approximation methods, including polynomial and radial basis functions. In this talk, I will explore how inadequate sampling can lead to parameter overfitting and introduce a class of greedy algorithms for generating effective sampling points. Additionally, I will discuss strategies to make these methods computationally efficient.