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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Yes, you can access Multivariate Algorithms and Information-Based Complexity by Fred J. Hickernell, Peter Kritzer, Fred J. Hickernell, Peter Kritzer in PDF and/or ePUB format, as well as other popular books in Mathematik & Angewandte Mathematik. We have over one million books available in our catalogue for you to explore.

Information

Publisher

De Gruyter

Year

2020

ISBN

9783110633153

Edition

Topic

Mathematik

Subtopic

Angewandte Mathematik

Title Page
Copyright
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 ε-Superposition and truncation dimensions, and multivariate method for ∞-variate linear problems
7 Adaptive approximation for multivariate linear problems with inputs lying in a cone