Multivariate Algorithms and Information-Based Complexity

Published by De Gruyter 2020

Multivariate Algorithms and Information-Based Complexity

Edited by: Fred J. Hickernell and Peter Kritzer

Volume 27 in the series Radon Series on Computational and Applied Mathematics

https://doi.org/10.1515/9783110635461

Overview
Contents

About this book

The contributions by leading experts in this book focus on a variety of topics of current interest related to information-based complexity, ranging from function approximation, numerical integration, numerical methods for the sphere, and algorithms with random information, to Bayesian probabilistic numerical methods and numerical methods for stochastic differential equations.

Presents the state-of-the-art around information-based complexity
Includes contributions by leading experts in the field
Covers both theoretical and numerical results as well as their applications

Author / Editor information

Fred J. Hickernell, Illinois Institute of Technology, USA; Peter Kritzer, Johann Radon Institute, Austria.

Topics

Frontmatter Publicly Available Download PDF	I
Preface: Multivariate algorithms and information-based complexity Publicly Available Download PDF	V
Contents Publicly Available Download PDF	IX
1. The control variate integration algorithm for multivariate functions defined at scattered data points Jeremy Dewar, James M. Hyman and Mu Tian Requires Authentication Unlicensed Licensed Download PDF	1
2. An adaptive random bit multilevel algorithm for SDEs Michael B. Giles, Mario Hefter, Lukas Mayer and Klaus Ritter Requires Authentication Unlicensed Licensed Download PDF	15
3. RBF-based penalized least-squares approximation of noisy scattered data on the sphere Kerstin Hesse Requires Authentication Unlicensed Licensed Download PDF	33
4. On the power of random information Aicke Hinrichs, David Krieg, Erich Novak, Joscha Prochno and Mario Ullrich Requires Authentication Unlicensed Licensed Download PDF	43
5. Optimality criteria for probabilistic numerical methods C. J. Oates, J. Cockayne, D. Prangle, T. J. Sullivan and M. Girolami Requires Authentication Unlicensed Licensed Download PDF	65
6. ε-Superposition and truncation dimensions, and multivariate method for∞-variate linear problems G. W. Wasilkowski Requires Authentication Unlicensed Licensed Download PDF	89
7. Adaptive approximation for multivariate linear problems with inputs lying in a cone Yuhan Ding, Fred J. Hickernell, Peter Kritzer and Simon Mak Requires Authentication Unlicensed Licensed Download PDF	109

(Deutsch)

Language: English
Publisher: De Gruyter
Audience: Researchers and graduate students in applied and numerical mathematics and in computer science.
Pages
- Front matter: 10
- Main content: 148
Illustrations
- Illustrations: 4
- Coloured Illustrations: 16
Keywords: Bayes-Verfahren; Komplexitätstheorie; Multivariate Daten; Numerische Integration; Numerisches Verfahren

eBook

Published: June 8, 2020
ISBN: 9783110635461

Hardcover

Published: May 18, 2020
ISBN: 9783110633115