Algorithms For Approximation

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The Design of Approximation Algorithms

Author : David P. Williamson
Publisher : Cambridge University Press
ISBN 13 : 9780521195270
Total Pages : 518 pages
Book Rating : 4.1/5 (952 download)

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Book Synopsis The Design of Approximation Algorithms by : David P. Williamson

Download or read book The Design of Approximation Algorithms written by David P. Williamson and published by Cambridge University Press. This book was released on 2011-04-26 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete optimization problems are everywhere, from traditional operations research planning problems, such as scheduling, facility location, and network design; to computer science problems in databases; to advertising issues in viral marketing. Yet most such problems are NP-hard. Thus unless P = NP, there are no efficient algorithms to find optimal solutions to such problems. This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. The book is organized around central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization. Each chapter in the first part of the book is devoted to a single algorithmic technique, which is then applied to several different problems. The second part revisits the techniques but offers more sophisticated treatments of them. The book also covers methods for proving that optimization problems are hard to approximate. Designed as a textbook for graduate-level algorithms courses, the book will also serve as a reference for researchers interested in the heuristic solution of discrete optimization problems.

Approximation Algorithms

Author : Vijay V. Vazirani
Publisher : Springer Science & Business Media
ISBN 13 : 3662045656
Total Pages : 380 pages
Book Rating : 4.6/5 (62 download)

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Book Synopsis Approximation Algorithms by : Vijay V. Vazirani

Download or read book Approximation Algorithms written by Vijay V. Vazirani and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering the basic techniques used in the latest research work, the author consolidates progress made so far, including some very recent and promising results, and conveys the beauty and excitement of work in the field. He gives clear, lucid explanations of key results and ideas, with intuitive proofs, and provides critical examples and numerous illustrations to help elucidate the algorithms. Many of the results presented have been simplified and new insights provided. Of interest to theoretical computer scientists, operations researchers, and discrete mathematicians.

Geometric Approximation Algorithms

Author : Sariel Har-Peled
Publisher : American Mathematical Soc.
ISBN 13 : 0821849115
Total Pages : 378 pages
Book Rating : 4.8/5 (218 download)

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Book Synopsis Geometric Approximation Algorithms by : Sariel Har-Peled

Download or read book Geometric Approximation Algorithms written by Sariel Har-Peled and published by American Mathematical Soc.. This book was released on 2011 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exact algorithms for dealing with geometric objects are complicated, hard to implement in practice, and slow. Over the last 20 years a theory of geometric approximation algorithms has emerged. These algorithms tend to be simple, fast, and more robust than their exact counterparts. This book is the first to cover geometric approximation algorithms in detail. In addition, more traditional computational geometry techniques that are widely used in developing such algorithms, like sampling, linear programming, etc., are also surveyed. Other topics covered include approximate nearest-neighbor search, shape approximation, coresets, dimension reduction, and embeddings. The topics covered are relatively independent and are supplemented by exercises. Close to 200 color figures are included in the text to illustrate proofs and ideas.

Approximation Algorithms and Semidefinite Programming

Author : Bernd Gärtner
Publisher : Springer Science & Business Media
ISBN 13 : 3642220150
Total Pages : 253 pages
Book Rating : 4.6/5 (422 download)

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Book Synopsis Approximation Algorithms and Semidefinite Programming by : Bernd Gärtner

Download or read book Approximation Algorithms and Semidefinite Programming written by Bernd Gärtner and published by Springer Science & Business Media. This book was released on 2012-01-10 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Semidefinite programs constitute one of the largest classes of optimization problems that can be solved with reasonable efficiency - both in theory and practice. They play a key role in a variety of research areas, such as combinatorial optimization, approximation algorithms, computational complexity, graph theory, geometry, real algebraic geometry and quantum computing. This book is an introduction to selected aspects of semidefinite programming and its use in approximation algorithms. It covers the basics but also a significant amount of recent and more advanced material. There are many computational problems, such as MAXCUT, for which one cannot reasonably expect to obtain an exact solution efficiently, and in such case, one has to settle for approximate solutions. For MAXCUT and its relatives, exciting recent results suggest that semidefinite programming is probably the ultimate tool. Indeed, assuming the Unique Games Conjecture, a plausible but as yet unproven hypothesis, it was shown that for these problems, known algorithms based on semidefinite programming deliver the best possible approximation ratios among all polynomial-time algorithms. This book follows the “semidefinite side” of these developments, presenting some of the main ideas behind approximation algorithms based on semidefinite programming. It develops the basic theory of semidefinite programming, presents one of the known efficient algorithms in detail, and describes the principles of some others. It also includes applications, focusing on approximation algorithms.

Design and Analysis of Approximation Algorithms

Author : Ding-Zhu Du
Publisher : Springer Science & Business Media
ISBN 13 : 1461417015
Total Pages : 450 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Design and Analysis of Approximation Algorithms by : Ding-Zhu Du

Download or read book Design and Analysis of Approximation Algorithms written by Ding-Zhu Du and published by Springer Science & Business Media. This book was released on 2011-11-18 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to be used as a textbook for graduate students studying theoretical computer science. It can also be used as a reference book for researchers in the area of design and analysis of approximation algorithms. Design and Analysis of Approximation Algorithms is a graduate course in theoretical computer science taught widely in the universities, both in the United States and abroad. There are, however, very few textbooks available for this course. Among those available in the market, most books follow a problem-oriented format; that is, they collected many important combinatorial optimization problems and their approximation algorithms, and organized them based on the types, or applications, of problems, such as geometric-type problems, algebraic-type problems, etc. Such arrangement of materials is perhaps convenient for a researcher to look for the problems and algorithms related to his/her work, but is difficult for a student to capture the ideas underlying the various algorithms. In the new book proposed here, we follow a more structured, technique-oriented presentation. We organize approximation algorithms into different chapters, based on the design techniques for the algorithms, so that the reader can study approximation algorithms of the same nature together. It helps the reader to better understand the design and analysis techniques for approximation algorithms, and also helps the teacher to present the ideas and techniques of approximation algorithms in a more unified way.

Approximation Algorithms for NP-hard Problems

Author : Dorit S. Hochbaum
Publisher : Course Technology
ISBN 13 :
Total Pages : 632 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Approximation Algorithms for NP-hard Problems by : Dorit S. Hochbaum

Download or read book Approximation Algorithms for NP-hard Problems written by Dorit S. Hochbaum and published by Course Technology. This book was released on 1997 with total page 632 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to fully address the study of approximation algorithms as a tool for coping with intractable problems. With chapters contributed by leading researchers in the field, this book introduces unifying techniques in the analysis of approximation algorithms. APPROXIMATION ALGORITHMS FOR NP-HARD PROBLEMS is intended for computer scientists and operations researchers interested in specific algorithm implementations, as well as design tools for algorithms. Among the techniques discussed: the use of linear programming, primal-dual techniques in worst-case analysis, semidefinite programming, computational geometry techniques, randomized algorithms, average-case analysis, probabilistically checkable proofs and inapproximability, and the Markov Chain Monte Carlo method. The text includes a variety of pedagogical features: definitions, exercises, open problems, glossary of problems, index, and notes on how best to use the book.

Approximation and Optimization

Author : Ioannis C. Demetriou
Publisher : Springer
ISBN 13 : 3030127672
Total Pages : 237 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Approximation and Optimization by : Ioannis C. Demetriou

Download or read book Approximation and Optimization written by Ioannis C. Demetriou and published by Springer. This book was released on 2019-05-10 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the development of approximation-related algorithms and their relevant applications. Individual contributions are written by leading experts and reflect emerging directions and connections in data approximation and optimization. Chapters discuss state of the art topics with highly relevant applications throughout science, engineering, technology and social sciences. Academics, researchers, data science practitioners, business analysts, social sciences investigators and graduate students will find the number of illustrations, applications, and examples provided useful. This volume is based on the conference Approximation and Optimization: Algorithms, Complexity, and Applications, which was held in the National and Kapodistrian University of Athens, Greece, June 29–30, 2017. The mix of survey and research content includes topics in approximations to discrete noisy data; binary sequences; design of networks and energy systems; fuzzy control; large scale optimization; noisy data; data-dependent approximation; networked control systems; machine learning ; optimal design; no free lunch theorem; non-linearly constrained optimization; spectroscopy.

Handbook of Approximation Algorithms and Metaheuristics

Author : Teofilo F. Gonzalez
Publisher : CRC Press
ISBN 13 : 1351236407
Total Pages : 840 pages
Book Rating : 4.3/5 (512 download)

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Book Synopsis Handbook of Approximation Algorithms and Metaheuristics by : Teofilo F. Gonzalez

Download or read book Handbook of Approximation Algorithms and Metaheuristics written by Teofilo F. Gonzalez and published by CRC Press. This book was released on 2018-05-15 with total page 840 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Approximation Algorithms and Metaheuristics, Second Edition reflects the tremendous growth in the field, over the past two decades. Through contributions from leading experts, this handbook provides a comprehensive introduction to the underlying theory and methodologies, as well as the various applications of approximation algorithms and metaheuristics. Volume 1 of this two-volume set deals primarily with methodologies and traditional applications. It includes restriction, relaxation, local ratio, approximation schemes, randomization, tabu search, evolutionary computation, local search, neural networks, and other metaheuristics. It also explores multi-objective optimization, reoptimization, sensitivity analysis, and stability. Traditional applications covered include: bin packing, multi-dimensional packing, Steiner trees, traveling salesperson, scheduling, and related problems. Volume 2 focuses on the contemporary and emerging applications of methodologies to problems in combinatorial optimization, computational geometry and graphs problems, as well as in large-scale and emerging application areas. It includes approximation algorithms and heuristics for clustering, networks (sensor and wireless), communication, bioinformatics search, streams, virtual communities, and more. About the Editor Teofilo F. Gonzalez is a professor emeritus of computer science at the University of California, Santa Barbara. He completed his Ph.D. in 1975 from the University of Minnesota. He taught at the University of Oklahoma, the Pennsylvania State University, and the University of Texas at Dallas, before joining the UCSB computer science faculty in 1984. He spent sabbatical leaves at the Monterrey Institute of Technology and Higher Education and Utrecht University. He is known for his highly cited pioneering research in the hardness of approximation; for his sublinear and best possible approximation algorithm for k-tMM clustering; for introducing the open-shop scheduling problem as well as algorithms for its solution that have found applications in numerous research areas; as well as for his research on problems in the areas of job scheduling, graph algorithms, computational geometry, message communication, wire routing, etc.

Low Rank Approximation

Author : Ivan Markovsky
Publisher : Springer Science & Business Media
ISBN 13 : 1447122275
Total Pages : 260 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Low Rank Approximation by : Ivan Markovsky

Download or read book Low Rank Approximation written by Ivan Markovsky and published by Springer Science & Business Media. This book was released on 2011-11-19 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Approximation by Low-complexity Models details the theory, algorithms, and applications of structured low-rank approximation. Efficient local optimization methods and effective suboptimal convex relaxations for Toeplitz, Hankel, and Sylvester structured problems are presented. Much of the text is devoted to describing the applications of the theory including: system and control theory; signal processing; computer algebra for approximate factorization and common divisor computation; computer vision for image deblurring and segmentation; machine learning for information retrieval and clustering; bioinformatics for microarray data analysis; chemometrics for multivariate calibration; and psychometrics for factor analysis. Software implementation of the methods is given, making the theory directly applicable in practice. All numerical examples are included in demonstration files giving hands-on experience and exercises and MATLAB® examples assist in the assimilation of the theory.

Stochastic Approximation and Recursive Algorithms and Applications

Author : Harold Kushner
Publisher : Springer Science & Business Media
ISBN 13 : 038721769X
Total Pages : 478 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Stochastic Approximation and Recursive Algorithms and Applications by : Harold Kushner

Download or read book Stochastic Approximation and Recursive Algorithms and Applications written by Harold Kushner and published by Springer Science & Business Media. This book was released on 2006-05-04 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged. It contains many additional applications and results as well as more detailed discussion.

Randomized Algorithms: Approximation, Generation, and Counting

Author : Russ Bubley
Publisher : Springer Science & Business Media
ISBN 13 : 1447106954
Total Pages : 167 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Randomized Algorithms: Approximation, Generation, and Counting by : Russ Bubley

Download or read book Randomized Algorithms: Approximation, Generation, and Counting written by Russ Bubley and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomized Algorithms discusses two problems of fine pedigree: counting and generation, both of which are of fundamental importance to discrete mathematics and probability. When asking questions like "How many are there?" and "What does it look like on average?" of families of combinatorial structures, answers are often difficult to find -- we can be blocked by seemingly intractable algorithms. Randomized Algorithms shows how to get around the problem of intractability with the Markov chain Monte Carlo method, as well as highlighting the method's natural limits. It uses the technique of coupling before introducing "path coupling" a new technique which radically simplifies and improves upon previous methods in the area.

Approximation and Online Algorithms

Author : Evripidis Bampis
Publisher : Springer Nature
ISBN 13 : 3030394794
Total Pages : 253 pages
Book Rating : 4.0/5 (33 download)

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Book Synopsis Approximation and Online Algorithms by : Evripidis Bampis

Download or read book Approximation and Online Algorithms written by Evripidis Bampis and published by Springer Nature. This book was released on 2020-01-24 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed workshop post-proceedings of the 17th International Workshop on Approximation and Online Algorithms, WAOA 2019, held in Munich, Germany, in September 2019 as part of ALGO 2019. The 16 revised full papers presented together with one invited paper in this book were carefully reviewed and selected from 38 submissions. Topics of interest for WAOA 2018 were: graph algorithms; inapproximability results; network design; packing and covering; paradigms for the design and analysis of approximation and online algorithms; parameterized complexity; scheduling problems; algorithmic game theory; algorithmic trading; coloring and partitioning; competitive analysis; computational advertising; computational finance; cuts and connectivity; geometric problems; mechanism design; resource augmentation; and real-world applications.

Approximation and Online Algorithms

Author : Jochen Koenemann
Publisher : Springer Nature
ISBN 13 : 3030927024
Total Pages : 286 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Approximation and Online Algorithms by : Jochen Koenemann

Download or read book Approximation and Online Algorithms written by Jochen Koenemann and published by Springer Nature. This book was released on 2022-01-01 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed workshop post-proceedings of the 19th International Workshop on Approximation and Online Algorithms, WAOA 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually. The 16 revised full papers presented in this book were carefully reviewed and selected from 31 submissions. The papers focus on the design and analysis of algorithms for online and computationally hard problems.

Approximation Theory and Algorithms for Data Analysis

Author : Armin Iske
Publisher : Springer
ISBN 13 : 3030052281
Total Pages : 358 pages
Book Rating : 4.0/5 (3 download)

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Book Synopsis Approximation Theory and Algorithms for Data Analysis by : Armin Iske

Download or read book Approximation Theory and Algorithms for Data Analysis written by Armin Iske and published by Springer. This book was released on 2018-12-14 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook offers an accessible introduction to the theory and numerics of approximation methods, combining classical topics of approximation with recent advances in mathematical signal processing, and adopting a constructive approach, in which the development of numerical algorithms for data analysis plays an important role. The following topics are covered: * least-squares approximation and regularization methods * interpolation by algebraic and trigonometric polynomials * basic results on best approximations * Euclidean approximation * Chebyshev approximation * asymptotic concepts: error estimates and convergence rates * signal approximation by Fourier and wavelet methods * kernel-based multivariate approximation * approximation methods in computerized tomography Providing numerous supporting examples, graphical illustrations, and carefully selected exercises, this textbook is suitable for introductory courses, seminars, and distance learning programs on approximation for undergraduate students.

Algorithms - ESA '98

Author : Gianfranco Bilardi
Publisher : Springer
ISBN 13 : 3540685308
Total Pages : 524 pages
Book Rating : 4.5/5 (46 download)

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Book Synopsis Algorithms - ESA '98 by : Gianfranco Bilardi

Download or read book Algorithms - ESA '98 written by Gianfranco Bilardi and published by Springer. This book was released on 2003-07-30 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: 9

Integer Programming and Combinatorial Optimization

Author : Gerard Cornuejols
Publisher : Springer
ISBN 13 : 3540487778
Total Pages : 462 pages
Book Rating : 4.5/5 (44 download)

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Book Synopsis Integer Programming and Combinatorial Optimization by : Gerard Cornuejols

Download or read book Integer Programming and Combinatorial Optimization written by Gerard Cornuejols and published by Springer. This book was released on 2007-03-05 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Integer Programming and Combinatorial Optimization, IPCO'99, held in Graz, Austria, in June 1999. The 33 revised full papers presented were carefully reviewed and selected from a total of 99 submissions. Among the topics addressed are theoretical, computational, and application-oriented aspects of approximation algorithms, branch and bound algorithms, computational biology, computational complexity, computational geometry, cutting plane algorithms, diaphantine equations, geometry of numbers, graph and network algorithms, online algorithms, polyhedral combinatorics, scheduling, and semidefinite programs.

Approximation and Weak Convergence Methods for Random Processes, with Applications to Stochastic Systems Theory

Author : Harold Joseph Kushner
Publisher : MIT Press
ISBN 13 : 9780262110907
Total Pages : 296 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Approximation and Weak Convergence Methods for Random Processes, with Applications to Stochastic Systems Theory by : Harold Joseph Kushner

Download or read book Approximation and Weak Convergence Methods for Random Processes, with Applications to Stochastic Systems Theory written by Harold Joseph Kushner and published by MIT Press. This book was released on 1984 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: Control and communications engineers, physicists, and probability theorists, among others, will find this book unique. It contains a detailed development of approximation and limit theorems and methods for random processes and applies them to numerous problems of practical importance. In particular, it develops usable and broad conditions and techniques for showing that a sequence of processes converges to a Markov diffusion or jump process. This is useful when the natural physical model is quite complex, in which case a simpler approximation la diffusion process, for example) is usually made. The book simplifies and extends some important older methods and develops some powerful new ones applicable to a wide variety of limit and approximation problems. The theory of weak convergence of probability measures is introduced along with general and usable methods (for example, perturbed test function, martingale, and direct averaging) for proving tightness and weak convergence. Kushner's study begins with a systematic development of the method. It then treats dynamical system models that have state-dependent noise or nonsmooth dynamics. Perturbed Liapunov function methods are developed for stability studies of nonMarkovian problems and for the study of asymptotic distributions of non-Markovian systems. Three chapters are devoted to applications in control and communication theory (for example, phase-locked loops and adoptive filters). Smallnoise problems and an introduction to the theory of large deviations and applications conclude the book. Harold J. Kushner is Professor of Applied Mathematics and Engineering at Brown University and is one of the leading researchers in the area of stochastic processes concerned with analysis and synthesis in control and communications theory. This book is the sixth in The MIT Press Series in Signal Processing, Optimization, and Control, edited by Alan S. Willsky.