Operator-Adapted Wavelets, Fast Solvers, and Numerical Homogenization - From a Game Theoretic Approach to Numerical Approximation and Algorithm Design (Hardcover)

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.

General

Imprint:	Cambridge UniversityPress
Country of origin:	United Kingdom
Series:	Cambridge Monographs on Applied and Computational Mathematics
Release date:	October 2019
Authors:	Houman Owhadi • Clint Scovel
Dimensions:	252 x 178 x 27mm (L x W x T)
Format:	Hardcover
Pages:	488
ISBN-13:	978-1-108-48436-7
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > General theory of computing > Mathematical theory of computation Books > Science & Mathematics > Mathematics > Optimization > Game theory Books > Science & Mathematics > Mathematics > Applied mathematics > General
LSN:	1-108-48436-0
Barcode:	9781108484367

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