A stochastic extended Rippa’s algorithm for LpOCV

L. Ling, F. Marchetti*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

In kernel-based approximation, the tuning of the so-called shape parameter is a fundamental step for achieving an accurate reconstruction. Recently, the popular Rippa's algorithm Rippa (1999) [1] has been extended to a more general cross validation setting. In this work, we propose a modification of such extension with the aim of further reducing the computational costs. The resulting Stochastic Extended Rippa's Algorithm (SERA) is first detailed and then tested by means of various numerical experiments, which show its efficacy and effectiveness in different approximation settings.

Original languageEnglish
Article number107955
JournalApplied Mathematics Letters
Volume129
DOIs
Publication statusPublished - Jul 2022

Scopus Subject Areas

  • Applied Mathematics

User-Defined Keywords

  • Cross validation
  • Extended Rippa's Algorithm
  • RBF interpolation
  • Stochastic low-rank approximation

Fingerprint

Dive into the research topics of 'A stochastic extended Rippa’s algorithm for LpOCV'. Together they form a unique fingerprint.

Cite this