Sobolev seminorm of quadratic functions with applications to derivative-free optimization

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Abstract

This paper studies the H1 Sobolev seminorm of quadratic functions. The research is motivated by the least-norm interpolation that is widely used in derivative-free optimization. We express the H1 seminorm of a quadratic function explicitly in terms of the Hessian and the gradient when the underlying domain is a ball. The seminorm gives new insights into least-norm interpolation. It clarifies the analytical and geometrical meaning of the objective function in least-norm interpolation. We employ the seminorm to study the extended symmetric Broyden update proposed by Powell. Numerical results show that the new thoery helps improve the performance of the update. Apart from the theoretical results, we propose a new method of comparing derivative-free solvers, which is more convincing than merely counting the numbers of function evaluations.
Original languageEnglish
Pages (from-to)77-96
Number of pages20
JournalMathematical Programming
Volume146
Issue number1-2
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes

Keywords

  • Derivative-free optimization
  • Extended symmetric Broyden update
  • Least-norm interpolation
  • Sobolev seminorm

ASJC Scopus subject areas

  • Software
  • Mathematics(all)

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