Inherently Parallel Algorithms In Feasibility And Optimization And Their Applications

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Inherently Parallel Algorithms in Feasibility and Optimization and their Applications

Author : D. Butnariu
Publisher : Elsevier
ISBN 13 : 0080508766
Total Pages : 515 pages
Book Rating : 4.0/5 (85 download)

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Book Synopsis Inherently Parallel Algorithms in Feasibility and Optimization and their Applications by : D. Butnariu

Download or read book Inherently Parallel Algorithms in Feasibility and Optimization and their Applications written by D. Butnariu and published by Elsevier. This book was released on 2001-06-18 with total page 515 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Haifa 2000 Workshop on "Inherently Parallel Algorithms for Feasibility and Optimization and their Applications" brought together top scientists in this area. The objective of the Workshop was to discuss, analyze and compare the latest developments in this fast growing field of applied mathematics and to identify topics of research which are of special interest for industrial applications and for further theoretical study. Inherently parallel algorithms, that is, computational methods which are, by their mathematical nature, parallel, have been studied in various contexts for more than fifty years. However, it was only during the last decade that they have mostly proved their practical usefulness because new generations of computers made their implementation possible in order to solve complex feasibility and optimization problems involving huge amounts of data via parallel processing. These led to an accumulation of computational experience and theoretical information and opened new and challenging questions concerning the behavior of inherently parallel algorithms for feasibility and optimization, their convergence in new environments and in circumstances in which they were not considered before their stability and reliability. Several research groups all over the world focused on these questions and it was the general feeling among scientists involved in this effort that the time has come to survey the latest progress and convey a perspective for further development and concerted scientific investigations. Thus, the editors of this volume, with the support of the Israeli Academy for Sciences and Humanities, took the initiative of organizing a Workshop intended to bring together the leading scientists in the field. The current volume is the Proceedings of the Workshop representing the discussions, debates and communications that took place. Having all that information collected in a single book will provide mathematicians and engineers interested in the theoretical and practical aspects of the inherently parallel algorithms for feasibility and optimization with a tool for determining when, where and which algorithms in this class are fit for solving specific problems, how reliable they are, how they behave and how efficient they were in previous applications. Such a tool will allow software creators to choose ways of better implementing these methods by learning from existing experience.

Handbook of Parallel Computing and Statistics

Author : Erricos John Kontoghiorghes
Publisher : CRC Press
ISBN 13 : 9781420028683
Total Pages : 560 pages
Book Rating : 4.0/5 (286 download)

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Book Synopsis Handbook of Parallel Computing and Statistics by : Erricos John Kontoghiorghes

Download or read book Handbook of Parallel Computing and Statistics written by Erricos John Kontoghiorghes and published by CRC Press. This book was released on 2005-12-21 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technological improvements continue to push back the frontier of processor speed in modern computers. Unfortunately, the computational intensity demanded by modern research problems grows even faster. Parallel computing has emerged as the most successful bridge to this computational gap, and many popular solutions have emerged based on its concepts

Nonlinear Analysis and Optimization I

Author : Simeon Reich
Publisher : American Mathematical Soc.
ISBN 13 : 0821848348
Total Pages : 290 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Nonlinear Analysis and Optimization I by : Simeon Reich

Download or read book Nonlinear Analysis and Optimization I written by Simeon Reich and published by American Mathematical Soc.. This book was released on 2010 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume is the first of two volumes representing leading themes of current research in nonlinear analysis and optimization. The articles are written by prominent researchers in these two areas and bring the readers, advanced graduate students and researchers alike, to the frontline of the vigorous research in these important fields of mathematics. This volume contains articles on nonlinear analysis. Topics covered include the convex feasibility problem, fixed point theory, mathematical biology, Mosco stability, nonexpansive mapping theory, nonlinear partial differential equations, optimal control, the proximal point algorithm and semigroup theory. The companion volume (Contemporary Mathematics, Volume 514) is devoted to optimization. This book is co-published with Bar-Ilan University (Ramat-Gan, Israel). Table of Contents: A. S. Ackleh, K. Deng, and Q. Huang -- Existence-uniqueness results and difference approximations for an amphibian juvenile-adult model; S. Aizicovici, N. S. Papageorgiou, and V. Staicu -- Three nontrivial solutions for $p$-Laplacian Neumann problems with a concave nonlinearity near the origin; V. Barbu -- Optimal stabilizable feedback controller for Navier-Stokes equations; H. H. Bauschke and X. Wang -- Firmly nonexpansive and Kirszbraun-Valentine extensions: A constructive approach via monotone operator theory; R. E. Bruck -- On the random product of orthogonal projections in Hilbert space II; D. Butnariu, E. Resmerita, and S. Sabach -- A Mosco stability theorem for the generalized proximal mapping; A. Cegielski -- Generalized relaxations of nonexpansive operators and convex feasibility problems; Y. Censor and A. Segal -- Sparse string-averaging and split common fixed points; T. Dominguez Benavides and S. Phothi -- Genericity of the fixed point property for reflexive spaces under renormings; K. Goebel and B. Sims -- Mean Lipschitzian mappings; T. Ibaraki and W. Takahashi -- Generalized nonexpansive mappings and a proximal-type algorithm in Banach spaces; W. Kaczor, T. Kuczumow, and N. Michalska -- The common fixed point set of commuting nonexpansive mapping in Cartesian products of weakly compact convex sets; L. Leu'tean -- Nonexpansive iterations in uniformly convex $W$-hyperbolic spaces; G. Lopez, V. Martin-Marquez, and H.-K. Xu -- Halpern's iteration for nonexpansive mappings; J. W. Neuberger -- Lie generators for local semigroups; H.-K. Xu -- An alternative regularization method for nonexpansive mappings with applications. (CONM/513)

Feasibility and Infeasibility in Optimization:

Author : John W. Chinneck
Publisher : Springer Science & Business Media
ISBN 13 : 0387749322
Total Pages : 283 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Feasibility and Infeasibility in Optimization: by : John W. Chinneck

Download or read book Feasibility and Infeasibility in Optimization: written by John W. Chinneck and published by Springer Science & Business Media. This book was released on 2007-10-25 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written by a world leader in the field and aimed at researchers in applied and engineering sciences, this brilliant text has as its main goal imparting an understanding of the methods so that practitioners can make immediate use of existing algorithms and software, and so that researchers can extend the state of the art and find new applications. It includes algorithms on seeking feasibility and analyzing infeasibility, as well as describing new and surprising applications.

Optimization for Machine Learning

Author : Suvrit Sra
Publisher : MIT Press
ISBN 13 : 026201646X
Total Pages : 509 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Optimization for Machine Learning by : Suvrit Sra

Download or read book Optimization for Machine Learning written by Suvrit Sra and published by MIT Press. This book was released on 2012 with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both communities. The interplay between optimization and machine learning is one of the most important developments in modern computational science. Optimization formulations and methods are proving to be vital in designing algorithms to extract essential knowledge from huge volumes of data. Machine learning, however, is not simply a consumer of optimization technology but a rapidly evolving field that is itself generating new optimization ideas. This book captures the state of the art of the interaction between optimization and machine learning in a way that is accessible to researchers in both fields. Optimization approaches have enjoyed prominence in machine learning because of their wide applicability and attractive theoretical properties. The increasing complexity, size, and variety of today's machine learning models call for the reassessment of existing assumptions. This book starts the process of reassessment. It describes the resurgence in novel contexts of established frameworks such as first-order methods, stochastic approximations, convex relaxations, interior-point methods, and proximal methods. It also devotes attention to newer themes such as regularized optimization, robust optimization, gradient and subgradient methods, splitting techniques, and second-order methods. Many of these techniques draw inspiration from other fields, including operations research, theoretical computer science, and subfields of optimization. The book will enrich the ongoing cross-fertilization between the machine learning community and these other fields, and within the broader optimization community.

Infinite Products of Operators and Their Applications

Author : Simeon Reich
Publisher : American Mathematical Soc.
ISBN 13 : 1470414805
Total Pages : 266 pages
Book Rating : 4.4/5 (74 download)

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Book Synopsis Infinite Products of Operators and Their Applications by : Simeon Reich

Download or read book Infinite Products of Operators and Their Applications written by Simeon Reich and published by American Mathematical Soc.. This book was released on 2015-03-30 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the proceedings of the workshop on Infinite Products of Operators and Their Applications, held from May 21-24, 2012, at the Technion-Israel Institute of Technology, Haifa, Israel. The papers cover many different topics regarding infinite products of operators and their applications: projection methods for solving feasibility and best approximation problems, arbitrarily slow convergence of sequences of linear operators, monotone operators, proximal point algorithms for finding zeros of maximal monotone operators in the presence of computational errors, the Pascoletti-Serafini problem, remetrization for infinite families of mappings, Poisson's equation for mean ergodic operators, vector-valued metrics in fixed point theory, contractivity of infinite products and mean convergence theorems for generalized nonspreading mappings. This book is co-published with Bar-Ilan University (Ramat-Gan, Israel).

Fixed-Point Algorithms for Inverse Problems in Science and Engineering

Author : Heinz H. Bauschke
Publisher : Springer Science & Business Media
ISBN 13 : 1441995692
Total Pages : 409 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Fixed-Point Algorithms for Inverse Problems in Science and Engineering by : Heinz H. Bauschke

Download or read book Fixed-Point Algorithms for Inverse Problems in Science and Engineering written by Heinz H. Bauschke and published by Springer Science & Business Media. This book was released on 2011-05-27 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Fixed-Point Algorithms for Inverse Problems in Science and Engineering" presents some of the most recent work from top-notch researchers studying projection and other first-order fixed-point algorithms in several areas of mathematics and the applied sciences. The material presented provides a survey of the state-of-the-art theory and practice in fixed-point algorithms, identifying emerging problems driven by applications, and discussing new approaches for solving these problems. This book incorporates diverse perspectives from broad-ranging areas of research including, variational analysis, numerical linear algebra, biotechnology, materials science, computational solid-state physics, and chemistry. Topics presented include: Theory of Fixed-point algorithms: convex analysis, convex optimization, subdifferential calculus, nonsmooth analysis, proximal point methods, projection methods, resolvent and related fixed-point theoretic methods, and monotone operator theory. Numerical analysis of fixed-point algorithms: choice of step lengths, of weights, of blocks for block-iterative and parallel methods, and of relaxation parameters; regularization of ill-posed problems; numerical comparison of various methods. Areas of Applications: engineering (image and signal reconstruction and decompression problems), computer tomography and radiation treatment planning (convex feasibility problems), astronomy (adaptive optics), crystallography (molecular structure reconstruction), computational chemistry (molecular structure simulation) and other areas. Because of the variety of applications presented, this book can easily serve as a basis for new and innovated research and collaboration.

Approximate Solutions of Common Fixed-Point Problems

Author : Alexander J. Zaslavski
Publisher : Springer
ISBN 13 : 3319332554
Total Pages : 454 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis Approximate Solutions of Common Fixed-Point Problems by : Alexander J. Zaslavski

Download or read book Approximate Solutions of Common Fixed-Point Problems written by Alexander J. Zaslavski and published by Springer. This book was released on 2016-06-30 with total page 454 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents results on the convergence behavior of algorithms which are known as vital tools for solving convex feasibility problems and common fixed point problems. The main goal for us in dealing with a known computational error is to find what approximate solution can be obtained and how many iterates one needs to find it. According to know results, these algorithms should converge to a solution. In this exposition, these algorithms are studied, taking into account computational errors which remain consistent in practice. In this case the convergence to a solution does not take place. We show that our algorithms generate a good approximate solution if computational errors are bounded from above by a small positive constant. Beginning with an introduction, this monograph moves on to study: · dynamic string-averaging methods for common fixed point problems in a Hilbert space · dynamic string methods for common fixed point problems in a metric space“/p> · dynamic string-averaging version of the proximal algorithm · common fixed point problems in metric spaces · common fixed point problems in the spaces with distances of the Bregman type · a proximal algorithm for finding a common zero of a family of maximal monotone operators · subgradient projections algorithms for convex feasibility problems in Hilbert spaces

Parallel Processing for Scientific Computing

Author : Michael A. Heroux
Publisher : SIAM
ISBN 13 : 0898716195
Total Pages : 407 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Parallel Processing for Scientific Computing by : Michael A. Heroux

Download or read book Parallel Processing for Scientific Computing written by Michael A. Heroux and published by SIAM. This book was released on 2006-01-01 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific computing has often been called the third approach to scientific discovery, emerging as a peer to experimentation and theory. Historically, the synergy between experimentation and theory has been well understood: experiments give insight into possible theories, theories inspire experiments, experiments reinforce or invalidate theories, and so on. As scientific computing has evolved to produce results that meet or exceed the quality of experimental and theoretical results, it has become indispensable.Parallel processing has been an enabling technology in scientific computing for more than 20 years. This book is the first in-depth discussion of parallel computing in 10 years; it reflects the mix of topics that mathematicians, computer scientists, and computational scientists focus on to make parallel processing effective for scientific problems. Presently, the impact of parallel processing on scientific computing varies greatly across disciplines, but it plays a vital role in most problem domains and is absolutely essential in many of them. Parallel Processing for Scientific Computing is divided into four parts: The first concerns performance modeling, analysis, and optimization; the second focuses on parallel algorithms and software for an array of problems common to many modeling and simulation applications; the third emphasizes tools and environments that can ease and enhance the process of application development; and the fourth provides a sampling of applications that require parallel computing for scaling to solve larger and realistic models that can advance science and engineering. This edited volume serves as an up-to-date reference for researchers and application developers on the state of the art in scientific computing. It also serves as an excellent overview and introduction, especially for graduate and senior-level undergraduate students interested in computational modeling and simulation and related computer science and applied mathematics aspects.Contents List of Figures; List of Tables; Preface; Chapter 1: Frontiers of Scientific Computing: An Overview; Part I: Performance Modeling, Analysis and Optimization. Chapter 2: Performance Analysis: From Art to Science; Chapter 3: Approaches to Architecture-Aware Parallel Scientific Computation; Chapter 4: Achieving High Performance on the BlueGene/L Supercomputer; Chapter 5: Performance Evaluation and Modeling of Ultra-Scale Systems; Part II: Parallel Algorithms and Enabling Technologies. Chapter 6: Partitioning and Load Balancing; Chapter 7: Combinatorial Parallel and Scientific Computing; Chapter 8: Parallel Adaptive Mesh Refinement; Chapter 9: Parallel Sparse Solvers, Preconditioners, and Their Applications; Chapter 10: A Survey of Parallelization Techniques for Multigrid Solvers; Chapter 11: Fault Tolerance in Large-Scale Scientific Computing; Part III: Tools and Frameworks for Parallel Applications. Chapter 12: Parallel Tools and Environments: A Survey; Chapter 13: Parallel Linear Algebra Software; Chapter 14: High-Performance Component Software Systems; Chapter 15: Integrating Component-Based Scientific Computing Software; Part IV: Applications of Parallel Computing. Chapter 16: Parallel Algorithms for PDE-Constrained Optimization; Chapter 17: Massively Parallel Mixed-Integer Programming; Chapter 18: Parallel Methods and Software for Multicomponent Simulations; Chapter 19: Parallel Computational Biology; Chapter 20: Opportunities and Challenges for Parallel Computing in Science and Engineering; Index.

10th International Symposium on Process Systems Engineering - PSE2009

Author : Rita Maria de Brito Alves
Publisher : Elsevier
ISBN 13 : 9780444534736
Total Pages : 2165 pages
Book Rating : 4.5/5 (347 download)

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Book Synopsis 10th International Symposium on Process Systems Engineering - PSE2009 by : Rita Maria de Brito Alves

Download or read book 10th International Symposium on Process Systems Engineering - PSE2009 written by Rita Maria de Brito Alves and published by Elsevier. This book was released on 2009-08-05 with total page 2165 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the proceedings of the 10e of a series of international symposia on process systems engineering (PSE) initiated in 1982. The special focus of PSE09 is how PSE methods can support sustainable resource systems and emerging technologies in the areas of green engineering. * Contains fully searchable CD of all printed contributions * Focus on sustainable green engineering * 9 Plenary papers, 21 Keynote lectures by leading experts in the field

10th International Symposium on Process Systems Engineering

Author : Rita Maria de Brito Alves
Publisher : Elsevier
ISBN 13 : 0444534350
Total Pages : 1229 pages
Book Rating : 4.4/5 (445 download)

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Book Synopsis 10th International Symposium on Process Systems Engineering by : Rita Maria de Brito Alves

Download or read book 10th International Symposium on Process Systems Engineering written by Rita Maria de Brito Alves and published by Elsevier. This book was released on 2009 with total page 1229 pages. Available in PDF, EPUB and Kindle. Book excerpt: The 10th International Symposium on Process Systems Engineering, PSE'09, will be held in Salvador-Bahia, Brazil on August 16-20, 2009. The special focus of PSE 2009 is Sustainability, Energy and Engineering. PSE 2009 is the tenth in the triennial series of international symposia on process systems engineering initiated in 1982. The meeting is brings together the worldwide PSE community of researchers and practitioners who are involved in the creation and application of computing-based methodologies for planning, design, operation, control and maintenance of chemical and petrochemical process industries. PSE'09 will look at how the PSE methods and tools can support sustainable resource systems and emerging technologies in the areas of green engineering: environmentally conscious design of industrial processes. PSE methods and tools support: - sustainable resource systems - emerging technologies in the areas of green engineering - environmentally conscious design of industrial processes

Parallel Optimization

Author : Department of Mathematics and Computer Science Yair Censor
Publisher : Oxford University Press on Demand
ISBN 13 : 9780195100624
Total Pages : 574 pages
Book Rating : 4.1/5 (6 download)

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Book Synopsis Parallel Optimization by : Department of Mathematics and Computer Science Yair Censor

Download or read book Parallel Optimization written by Department of Mathematics and Computer Science Yair Censor and published by Oxford University Press on Demand. This book was released on 1997 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a unique pathway to methods of parallel optimization by introducing parallel computing ideas into both optimization theory and into some numerical algorithms for large-scale optimization problems. The three parts of the book bring together relevant theory, careful study of algorithms, and modeling of significant real world problems such as image reconstruction, radiation therapy treatment planning, financial planning, transportation and multi-commodity network flow problems, planning under uncertainty, and matrix balancing problems.

Algorithms for Solving Common Fixed Point Problems

Author : Alexander J. Zaslavski
Publisher : Springer
ISBN 13 : 3319774379
Total Pages : 316 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Algorithms for Solving Common Fixed Point Problems by : Alexander J. Zaslavski

Download or read book Algorithms for Solving Common Fixed Point Problems written by Alexander J. Zaslavski and published by Springer. This book was released on 2018-05-02 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book details approximate solutions to common fixed point problems and convex feasibility problems in the presence of perturbations. Convex feasibility problems search for a common point of a finite collection of subsets in a Hilbert space; common fixed point problems pursue a common fixed point of a finite collection of self-mappings in a Hilbert space. A variety of algorithms are considered in this book for solving both types of problems, the study of which has fueled a rapidly growing area of research. This monograph is timely and highlights the numerous applications to engineering, computed tomography, and radiation therapy planning. Totaling eight chapters, this book begins with an introduction to foundational material and moves on to examine iterative methods in metric spaces. The dynamic string-averaging methods for common fixed point problems in normed space are analyzed in Chapter 3. Dynamic string methods, for common fixed point problems in a metric space are introduced and discussed in Chapter 4. Chapter 5 is devoted to the convergence of an abstract version of the algorithm which has been called component-averaged row projections (CARP). Chapter 6 studies a proximal algorithm for finding a common zero of a family of maximal monotone operators. Chapter 7 extends the results of Chapter 6 for a dynamic string-averaging version of the proximal algorithm. In Chapters 8 subgradient projections algorithms for convex feasibility problems are examined for infinite dimensional Hilbert spaces.

Convex Optimization Algorithms

Author : Dimitri Bertsekas
Publisher : Athena Scientific
ISBN 13 : 1886529280
Total Pages : 576 pages
Book Rating : 4.8/5 (865 download)

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Book Synopsis Convex Optimization Algorithms by : Dimitri Bertsekas

Download or read book Convex Optimization Algorithms written by Dimitri Bertsekas and published by Athena Scientific. This book was released on 2015-02-01 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and accessible presentation of algorithms for solving convex optimization problems. It relies on rigorous mathematical analysis, but also aims at an intuitive exposition that makes use of visualization where possible. This is facilitated by the extensive use of analytical and algorithmic concepts of duality, which by nature lend themselves to geometrical interpretation. The book places particular emphasis on modern developments, and their widespread applications in fields such as large-scale resource allocation problems, signal processing, and machine learning. The book is aimed at students, researchers, and practitioners, roughly at the first year graduate level. It is similar in style to the author's 2009"Convex Optimization Theory" book, but can be read independently. The latter book focuses on convexity theory and optimization duality, while the present book focuses on algorithmic issues. The two books share notation, and together cover the entire finite-dimensional convex optimization methodology. To facilitate readability, the statements of definitions and results of the "theory book" are reproduced without proofs in Appendix B.

Iterative Optimization in Inverse Problems

Author : Charles L. Byrne
Publisher : CRC Press
ISBN 13 : 1482222337
Total Pages : 302 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis Iterative Optimization in Inverse Problems by : Charles L. Byrne

Download or read book Iterative Optimization in Inverse Problems written by Charles L. Byrne and published by CRC Press. This book was released on 2014-02-12 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Iterative Optimization in Inverse Problems brings together a number of important iterative algorithms for medical imaging, optimization, and statistical estimation. It incorporates recent work that has not appeared in other books and draws on the author’s considerable research in the field, including his recently developed class of SUMMA algorithms. Related to sequential unconstrained minimization methods, the SUMMA class includes a wide range of iterative algorithms well known to researchers in various areas, such as statistics and image processing. Organizing the topics from general to more specific, the book first gives an overview of sequential optimization, the subclasses of auxiliary-function methods, and the SUMMA algorithms. The next three chapters present particular examples in more detail, including barrier- and penalty-function methods, proximal minimization, and forward-backward splitting. The author also focuses on fixed-point algorithms for operators on Euclidean space and then extends the discussion to include distance measures other than the usual Euclidean distance. In the final chapters, specific problems illustrate the use of iterative methods previously discussed. Most chapters contain exercises that introduce new ideas and make the book suitable for self-study. Unifying a variety of seemingly disparate algorithms, the book shows how to derive new properties of algorithms by comparing known properties of other algorithms. This unifying approach also helps researchers—from statisticians working on parameter estimation to image scientists processing scanning data to mathematicians involved in theoretical and applied optimization—discover useful related algorithms in areas outside of their expertise.

Iterative Methods for Fixed Point Problems in Hilbert Spaces

Author : Andrzej Cegielski
Publisher : Springer
ISBN 13 : 3642309011
Total Pages : 312 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis Iterative Methods for Fixed Point Problems in Hilbert Spaces by : Andrzej Cegielski

Download or read book Iterative Methods for Fixed Point Problems in Hilbert Spaces written by Andrzej Cegielski and published by Springer. This book was released on 2012-09-14 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Iterative methods for finding fixed points of non-expansive operators in Hilbert spaces have been described in many publications. In this monograph we try to present the methods in a consolidated way. We introduce several classes of operators, examine their properties, define iterative methods generated by operators from these classes and present general convergence theorems. On this basis we discuss the conditions under which particular methods converge. A large part of the results presented in this monograph can be found in various forms in the literature (although several results presented here are new). We have tried, however, to show that the convergence of a large class of iteration methods follows from general properties of some classes of operators and from some general convergence theorems.

A First Course in Optimization

Author : Charles L. Byrne
Publisher : CRC Press
ISBN 13 : 1482226561
Total Pages : 318 pages
Book Rating : 4.4/5 (822 download)

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Book Synopsis A First Course in Optimization by : Charles L. Byrne

Download or read book A First Course in Optimization written by Charles L. Byrne and published by CRC Press. This book was released on 2014-08-11 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: Give Your Students the Proper Groundwork for Future Studies in Optimization A First Course in Optimization is designed for a one-semester course in optimization taken by advanced undergraduate and beginning graduate students in the mathematical sciences and engineering. It teaches students the basics of continuous optimization and helps them better understand the mathematics from previous courses. The book focuses on general problems and the underlying theory. It introduces all the necessary mathematical tools and results. The text covers the fundamental problems of constrained and unconstrained optimization as well as linear and convex programming. It also presents basic iterative solution algorithms (such as gradient methods and the Newton–Raphson algorithm and its variants) and more general iterative optimization methods. This text builds the foundation to understand continuous optimization. It prepares students to study advanced topics found in the author’s companion book, Iterative Optimization in Inverse Problems, including sequential unconstrained iterative optimization methods.