On the Power of Standard Information for Weighted Approximation

G. W. Wasilkowski, H. Woźniakowski

Research output: Contribution to journalArticlepeer-review

36 Scopus citations

Abstract

We study weighted approximation of multivariate functions for classes of standard and linear information in the worst case and average case settings. Under natural assumptions, we show a relation between nth minimal errors for these two classes of information. This relation enables us to infer convergence and error bounds for standard information, as well as the equivalence of tractability and strong tractability for the two classes.

Original languageEnglish
Pages (from-to)417-434
Number of pages18
JournalFoundations of Computational Mathematics
Volume1
Issue number4
DOIs
StatePublished - Nov 2001

ASJC Scopus subject areas

  • Analysis
  • Computational Mathematics
  • Computational Theory and Mathematics
  • Applied Mathematics

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