Average-Case Analysis of Numerical Problems
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Beschreibung
The average-case analysis of numerical problems is the counterpart of the more traditional worst-case approach. The analysis of average error and cost leads to new insight on numerical problems as well as to new algorithms. The book provides a survey of results that were mainly obtained during the last 10 years and also contains new results. The problems under consideration include approximation/optimal recovery and numerical integration of univariate and multivariate functions as well as zero-finding and global optimization. Background material, e.g. on reproducing kernel Hilbert spaces and random fields, is provided.
Autor*in
Klaus Ritter
Themen in »Average-Case Analysis of Numerical Problems«
Bayesian numerical analysis Gaussian measure Numerical integration information-based complexity optimal numerical methods spatial statistics
Stimmen zu »Average-Case Analysis of Numerical Problems«
“The monograph is carefully written and gives a systematic up-to-date treatment of theoretical questions concerning the average-case analysis of numerical problems. It is helpful for both theoretical research and practical applications.” (Karel Najzar, zbMATH 0949.65146, 2022)
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