Paradigms Of Combinatorial Optimization

Author: Vangelis Th. Paschos
Publisher: John Wiley & Sons
ISBN: 1119015197
Size: 41.64 MB
Format: PDF
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Paradigms Of Combinatorial Optimization from the Author: Vangelis Th. Paschos. Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aim to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. Concepts of Combinatorial Optimization, is divided into three parts: - On the complexity of combinatorial optimization problems, presenting basics about worst-case and randomized complexity; - Classical solution methods, presenting the two most-known methods for solving hard combinatorial optimization problems, that are Branch-and-Bound and Dynamic Programming; - Elements from mathematical programming, presenting fundamentals from mathematical programming based methods that are in the heart of Operations Research since the origins of this field.

Applications Of Combinatorial Optimization

Author: Vangelis Th. Paschos
Publisher: John Wiley & Sons
ISBN: 1119015243
Size: 60.87 MB
Format: PDF, ePub, Docs
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Applications Of Combinatorial Optimization from the Author: Vangelis Th. Paschos. Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aim to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. Concepts of Combinatorial Optimization, is divided into three parts: - On the complexity of combinatorial optimization problems, presenting basics about worst-case and randomized complexity; - Classical solution methods, presenting the two most-known methods for solving hard combinatorial optimization problems, that are Branch-and-Bound and Dynamic Programming; - Elements from mathematical programming, presenting fundamentals from mathematical programming based methods that are in the heart of Operations Research since the origins of this field.

Concepts Of Combinatorial Optimization

Author: Vangelis Th. Paschos
Publisher: John Wiley & Sons
ISBN: 1119015073
Size: 36.22 MB
Format: PDF, ePub, Docs
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Concepts Of Combinatorial Optimization from the Author: Vangelis Th. Paschos. Combinatorial optimization is a multidisciplinary scientific area, lying in the interface of three major scientific domains: mathematics, theoretical computer science and management. The three volumes of the Combinatorial Optimization series aim to cover a wide range of topics in this area. These topics also deal with fundamental notions and approaches as with several classical applications of combinatorial optimization. Concepts of Combinatorial Optimization, is divided into three parts: - On the complexity of combinatorial optimization problems, presenting basics about worst-case and randomized complexity; - Classical solution methods, presenting the two most-known methods for solving hard combinatorial optimization problems, that are Branch-and-Bound and Dynamic Programming; - Elements from mathematical programming, presenting fundamentals from mathematical programming based methods that are in the heart of Operations Research since the origins of this field.

Computer Science Handbook Second Edition

Author: Allen B. Tucker
Publisher: CRC Press
ISBN: 0203494458
Size: 46.18 MB
Format: PDF, ePub
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Computer Science Handbook Second Edition from the Author: Allen B. Tucker. When you think about how far and fast computer science has progressed in recent years, it's not hard to conclude that a seven-year old handbook may fall a little short of the kind of reference today's computer scientists, software engineers, and IT professionals need. With a broadened scope, more emphasis on applied computing, and more than 70 chapters either new or significantly revised, the Computer Science Handbook, Second Edition is exactly the kind of reference you need. This rich collection of theory and practice fully characterizes the current state of the field and conveys the modern spirit, accomplishments, and direction of computer science. Highlights of the Second Edition: Coverage that reaches across all 11 subject areas of the discipline as defined in Computing Curricula 2001, now the standard taxonomy More than 70 chapters revised or replaced Emphasis on a more practical/applied approach to IT topics such as information management, net-centric computing, and human computer interaction More than 150 contributing authors--all recognized experts in their respective specialties New chapters on: cryptography computational chemistry computational astrophysics human-centered software development cognitive modeling transaction processing data compression scripting languages event-driven programming software architecture

Algorithmics For Hard Problems

Author: Juraj Hromkovič
Publisher: Springer Science & Business Media
ISBN: 3662046164
Size: 26.80 MB
Format: PDF, Kindle
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Algorithmics For Hard Problems from the Author: Juraj Hromkovič. An introduction to the methods of designing algorithms for hard computing tasks, concentrating mainly on approximate, randomized, and heuristic algorithms, and on the theoretical and experimental comparison of these approaches according to the requirements of the practice. This is the first book to systematically explain and compare all the main possibilities of attacking hard computing problems. It also closes the gap between theory and practice by providing at once a graduate textbook and a handbook for practitioners dealing with hard computing problems.

Distributed Sensor Networks Second Edition

Author: S. Sitharama Iyengar
Publisher: CRC Press
ISBN: 1439862877
Size: 10.16 MB
Format: PDF, ePub, Docs
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Distributed Sensor Networks Second Edition from the Author: S. Sitharama Iyengar. The best-selling Distributed Sensor Networks became the definitive guide to understanding this far-reaching technology. Preserving the excellence and accessibility of its predecessor, Distributed Sensor Networks, Second Edition once again provides all the fundamentals and applications in one complete, self-contained source. Ideal as a tutorial for students or as research material for engineers, the book gives readers up-to-date, practical insight on all aspects of the field. Revised and expanded, this second edition incorporates contributions from many veterans of the DARPA ISO SENSIT program as well as new material from distinguished researchers in the field. Sensor Networking and Applications focuses on sensor deployment and networking, adaptive tasking, self-configuration, and system control. In the expanded applications section, the book draws on the insight of practitioners in the field. Readers of this book may also be interested in Distributed Sensor Networks, Second Edition: Image and Sensor Signal Processing (ISBN: 9781439862827).

Foundations Of Genetic Algorithms

Author: Alden H. Wright
Publisher: Springer Science & Business Media
ISBN: 3540272372
Size: 67.79 MB
Format: PDF, Kindle
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Foundations Of Genetic Algorithms from the Author: Alden H. Wright. This book constitutes the refereed proceedings of the 8th workshop on the foundations of genetic algorithms, FOGA 2005, held in Aizu-Wakamatsu City, Japan, in January 2005. The 16 revised full papers presented provide an outstanding source of reference for the field of theoretical evolutionary computation including evolution strategies, evolutionary programming, and genetic programming, as well as the continuing growth in interactions with other fields such as mathematics, physics, and biology.

Algorithms And Theory Of Computation Handbook Second Edition Volume 2

Author: Mikhail J. Atallah
Publisher: CRC Press
ISBN: 9781584888215
Size: 72.43 MB
Format: PDF
View: 1151
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Algorithms And Theory Of Computation Handbook Second Edition Volume 2 from the Author: Mikhail J. Atallah. Algorithms and Theory of Computation Handbook, Second Edition: Special Topics and Techniques provides an up-to-date compendium of fundamental computer science topics and techniques. It also illustrates how the topics and techniques come together to deliver efficient solutions to important practical problems. Along with updating and revising many of the existing chapters, this second edition contains more than 15 new chapters. This edition now covers self-stabilizing and pricing algorithms as well as the theories of privacy and anonymity, databases, computational games, and communication networks. It also discusses computational topology, natural language processing, and grid computing and explores applications in intensity-modulated radiation therapy, voting, DNA research, systems biology, and financial derivatives. This best-selling handbook continues to help computer professionals and engineers find significant information on various algorithmic topics. The expert contributors clearly define the terminology, present basic results and techniques, and offer a number of current references to the in-depth literature. They also provide a glimpse of the major research issues concerning the relevant topics.

The Elements Of Statistical Learning

Author: Trevor Hastie
Publisher: Springer Science & Business Media
ISBN: 0387216065
Size: 60.20 MB
Format: PDF
View: 4735
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The Elements Of Statistical Learning from the Author: Trevor Hastie. During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.