A General Theory of Optimal Algorithms
A General Theory of Optimal Algorithms

Author: Joseph Frederick Traub

Publisher:

Published: 1980

Total Pages: 376

ISBN-13:

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The purpose of this monograph is to create a general framework for the study of optimal algorithms for problems that are solved approximately. For generality the setting is abstract, but we present many applications to practical problems and provide examples to illustrate concepts and major theorems. The work presented here is motivated by research in many fields. Influential have been questions, concepts, and results from complexity theory, algorithmic analysis, applied mathematics and numerical analysis, the mathematical theory of approximation (particularly the work on n-widths in the sense of Gelfand and Kolmogorov), applied approximation theory (particularly the theory of splines), as well as earlier work on optimal algorithms. But many of the questions we ask (see Overview) are new. We present a different view of algorithms and complexity and must request the reader's

Elements of the General Theory of Optimal Algorithms
Elements of the General Theory of Optimal Algorithms

Author: Ivan V. Sergienko

Publisher: Springer Nature

Published: 2022-01-11

Total Pages: 387

ISBN-13: 3030909085

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In this monograph, the authors develop a methodology that allows one to construct and substantiate optimal and suboptimal algorithms to solve problems in computational and applied mathematics. Throughout the book, the authors explore well-known and proposed algorithms with a view toward analyzing their quality and the range of their efficiency. The concept of the approach taken is based on several theories (of computations, of optimal algorithms, of interpolation, interlination, and interflatation of functions, to name several). Theoretical principles and practical aspects of testing the quality of algorithms and applied software, are a major component of the exposition. The computer technology in construction of T-efficient algorithms for computing ε-solutions to problems of computational and applied mathematics, is also explored. The readership for this monograph is aimed at scientists, postgraduate students, advanced students, and specialists dealing with issues of developing algorithmic and software support for the solution of problems of computational and applied mathematics.

Elements of the General Theory of Optimal Algorithms
Elements of the General Theory of Optimal Algorithms

Author: Ivan Vasilʹevich Sergienko

Publisher:

Published: 2021

Total Pages:

ISBN-13: 9783030909079

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In this monograph, the authors develop a methodology that allows one to construct and substantiate optimal and suboptimal algorithms to solve problems in computational and applied mathematics. Throughout the book, the authors explore well-known and proposed algorithms with a view toward analyzing their quality and the range of their efficiency. The concept of the approach taken is based on several theories (of computations, of optimal algorithms, of interpolation, interlination, and interflatation of functions, to name several). Theoretical principles and practical aspects of testing the quality of algorithms and applied software, are a major component of the exposition. The computer technology in construction of T-efficient algorithms for computing -solutions to problems of computational and applied mathematics, is also explored. The readership for this monograph is aimed at scientists, postgraduate students, advanced students, and specialists dealing with issues of developing algorithmic and software support for the solution of problems of computational and applied mathematics.

General Theory of Optimal Error Algorithms and Analytic Complexity. Part B. Iterative Information Model
General Theory of Optimal Error Algorithms and Analytic Complexity. Part B. Iterative Information Model

Author: J. F. Traub

Publisher:

Published: 1978

Total Pages: 97

ISBN-13:

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This is the second of a series of papers in which we construct an information based general theory of optimal error algorithms and analytic computational complexity and study applications of the general theory. In our first paper we studied a general information' model; here we study an 'iterative information' model. We give a general paradigm, based on the pre-image set of an information operator, for obtaining a lower bound on the error of any algorithm using this information. We show that the order of information provides an upper bound on the order of any algorithm using this information. This upper bound order leads to a lower bound on the complexity index.

General Theory of Optimal Error Algorithms and Analytic Complexity. Part A. General Information Model
General Theory of Optimal Error Algorithms and Analytic Complexity. Part A. General Information Model

Author: J. F. Traub

Publisher:

Published: 1977

Total Pages: 95

ISBN-13:

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This is the first of a series of papers constructing an information based general theory of optimal errors and analytic computational complexity. Among the applications are such traditionally diverse areas as approximation, boundary-value problems, quadrature, and nonlinear equations in a finite or infinite dimensional space. Traditionally algorithms are often derived by ad hoc criteria. The information based theory rationalizes the synthesis of algorithms by showing how to construct algorithms which minimize or nearly minimize the error. For certain classes of problems it shows how to construct algorithms (linear optimal error algorithms) which enjoy essentially optimal complexity with respect to all possible algorithms. The existence of strongly non-computable problems is demonstrated. In contrast with the gap theorem of recursively computable functions it is shown that every monotonic real function is the complexity of some problem.

Essays on the Complexity of Continuous Problems
Essays on the Complexity of Continuous Problems

Author: Erich Novak

Publisher: European Mathematical Society

Published: 2009

Total Pages: 112

ISBN-13: 9783037190692

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This book contains five essays on the complexity of continuous problems, written for a wider audience. The first four essays are based on talks presented in 2008 when Henryk Wozniakowski received an honorary doctoral degree from the Friedrich Schiller University of Jena. The focus is on the introduction and history of the complexity of continuous problems, as well as on recent progress concerning the complexity of high-dimensional numerical problems. The last essay provides a brief and informal introduction to the basic notions and concepts of information-based complexity addressed to a general readership.

A Course in Approximation Theory
A Course in Approximation Theory

Author: Elliott Ward Cheney

Publisher: American Mathematical Soc.

Published: 2009-01-13

Total Pages: 379

ISBN-13: 0821847988

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This textbook is designed for graduate students in mathematics, physics, engineering, and computer science. Its purpose is to guide the reader in exploring contemporary approximation theory. The emphasis is on multi-variable approximation theory, i.e., the approximation of functions in several variables, as opposed to the classical theory of functions in one variable. Most of the topics in the book, heretofore accessible only through research papers, are treated here from the basics to the currently active research, often motivated by practical problems arising in diverse applications such as science, engineering, geophysics, and business and economics. Among these topics are projections, interpolation paradigms, positive definite functions, interpolation theorems of Schoenberg and Micchelli, tomography, artificial neural networks, wavelets, thin-plate splines, box splines, ridge functions, and convolutions. An important and valuable feature of the book is the bibliography of almost 600 items directing the reader to important books and research papers. There are 438 problems and exercises scattered through the book allowing the student reader to get a better understanding of the subject.