Multivariate Algorithms and Information Based Complexity

This book PDF is perfect for those who love Mathematics genre, written by Fred J. Hickernell and published by Walter de Gruyter GmbH & Co KG which was released on 08 June 2020 with total hardcover pages 158. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Multivariate Algorithms and Information Based Complexity books below.

Multivariate Algorithms and Information Based Complexity
Author : Fred J. Hickernell
File Size : 43,5 Mb
Publisher : Walter de Gruyter GmbH & Co KG
Language : English
Release Date : 08 June 2020
ISBN : 9783110635461
Pages : 158 pages
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Multivariate Algorithms and Information Based Complexity by Fred J. Hickernell Book PDF Summary

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.

Multivariate Algorithms and Information Based Complexity

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.

Get Book
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Multivariate problems occur in many applications. These problems are defined on spaces of $d$-variate functions and $d$ can be huge--in the hundreds or even in the thousands. Some high-dimensional problems can be solved efficiently to within $\varepsilon$, i.e., the cost increases polynomially in $\varepsilon^{-1}$ and $d$. However,

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