In this paper we construct a hierarchy of multivariate polynomial approximation kernels via semidefinite programming. We give details on the implementation of the semidefinite programs defining the kernels. Finally, we show how a symmetry reduction may be performed to increase numerical tractability.
@article{arxiv.2203.05892,
title = {Construction of multivariate polynomial approximation kernels via semidefinite programming},
author = {Felix Kirschner and Etienne de Klerk},
journal= {arXiv preprint arXiv:2203.05892},
year = {2023}
}