Multivariate Algorithms and Information-Based Complexity
1st Edition
Published on 8. June 2020
X, 148 pages
978-3-11-063546-1 (ISBN)
Description
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.
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Additional editions
Fred J. Hickernell | Peter Kritzer
Multivariate Algorithms and Information-Based Complexity
E-Book
06/2020
1st Edition
De Gruyter
€154.95
Available for download
Fred J. Hickernell | Peter Kritzer
Multivariate Algorithms and Information-Based Complexity
Book
05/2020
1st Edition
De Gruyter
€154.95
Shipment within 7-9 days
Persons
Fred J. Hickernell , Illinois Institute of Technology, USA; Peter Kritzer , Johann Radon Institute, Austria.
Content
- Intro
- Preface: Multivariate algorithms and information-based complexity
- Contents
- 1. The control variate integration algorithm for multivariate functions defined at scattered data points
- 2. An adaptive random bit multilevel algorithm for SDEs
- 3. RBF-based penalized least-squares approximation of noisy scattered data on the sphere
- 4. On the power of random information
- 5. Optimality criteria for probabilistic numerical methods
- 6. e-Superposition and truncation dimensions, and multivariate method for8-variate linear problems
- 7. Adaptive approximation for multivariate linear problems with inputs lying in a cone
