Solving interpolation problems on surfaces stochastically and greedily

Meng Chen, Leevan Ling, Yichen Su

Research output: Contribution to journalJournal articlepeer-review

1 Citation (Scopus)


Choosing suitable shape parameters in the kernel-based interpolation problems is an open question, whose solutions can guarantee accuracy and numerical stability. In this paper, we study various ways to select Kernel’s shape parameters for interpolation problems on surfaces. In particular, we use exact and stochastically approximated cross validation approaches to select the shape parameters. When we solve the resultant matrix systems, we also deploy a greedy trial subspace selection algorithm to improve robustness. Numerical experiments are inserted along our discussion to demonstrate the feasibility and robustness of our proposed methods.

Original languageEnglish
Pages (from-to)26-36
Number of pages11
JournalDolomites Research Notes on Approximation
Issue number3
Publication statusPublished - Oct 2022

Scopus Subject Areas

  • Mathematics (miscellaneous)
  • Applied Mathematics


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