Name: Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization: From a Game Theoretic Approach to Numerical Approximation and Algorithm Design. On Applied and Computational Mathematics) (en Inglés)
SKU: 52094530
Price: 228.59 USD
Availability: InStock
Author: Houman Owhadi; Clint Scovel
ISBN: 9781108484367

portada Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization: From a Game Theoretic Approach to Numerical Approximation and Algorithm Design. On Applied and Computational Mathematics) (en Inglés)

Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization: From a Game Theoretic Approach to Numerical Approximation and Algorithm Design. On Applied and Computational Mathematics) (en Inglés)

Formato

Libro Físico

Editorial

Cambridge University Press

Autor

Houman Owhadi; Clint Scovel

Año

2019

Idioma

Inglés

N° páginas

488

Encuadernación

Tapa Dura

ISBN13

9781108484367

Categorías

Cálculo

Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization: From a Game Theoretic Approach to Numerical Approximation and Algorithm Design. On Applied and Computational Mathematics) (en Inglés)

Houman Owhadi; Clint Scovel (Autor) · Cambridge University Press · Tapa Dura

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Reseña del libro "Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization: From a Game Theoretic Approach to Numerical Approximation and Algorithm Design. On Applied and Computational Mathematics) (en Inglés)"

Although numerical approximation and statistical inference are traditionally covered as entirely separate subjects, they are intimately connected through the common purpose of making estimations with partial information. This book explores these connections from a game and decision theoretic perspective, showing how they constitute a pathway to developing simple and general methods for solving fundamental problems in both areas. It illustrates these interplays by addressing problems related to numerical homogenization, operator adapted wavelets, fast solvers, and Gaussian processes. This perspective reveals much of their essential anatomy and greatly facilitates advances in these areas, thereby appearing to establish a general principle for guiding the process of scientific discovery. This book is designed for graduate students, researchers, and engineers in mathematics, applied mathematics, and computer science, and particularly researchers interested in drawing on and developing this interface between approximation, inference, and learning.