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Approximate Iterative Algorithms
     

Approximate Iterative Algorithms

by Anthony Louis Almudevar, Edilson Fernandes de Arruda
 

Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error bounds and convergence rates, and for the optimal design of such algorithms.

Overview

Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error bounds and convergence rates, and for the optimal design of such algorithms. Techniques of functional analysis are used to derive analytical relationships between approximation methods and convergence properties for general classes of algorithms. The volume provides the necessary background in functional analysis and probability theory. Extensive applications to Markov decision processes are presented.

This volume is intended for mathematicians, engineers and computer scientists, who work on learning processes in numerical analysis and are involved with optimization, optimal control, decision analysis and machine learning.

Product Details

ISBN-13:
9780415621540
Publisher:
Taylor & Francis
Publication date:
03/19/2014
Pages:
372
Product dimensions:
6.80(w) x 9.70(h) x 1.00(d)

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