Computational Network Theory

Author : Matthias Dehmer
Publisher : John Wiley & Sons
ISBN 13 : 3527337245
Total Pages : 278 pages
Book Rating : 4.48/5 ( download)

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Download or read book Computational Network Theory written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2015-11-16 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive introduction to computational network theory as a branch of network theory builds on the understanding that such networks are a tool to derive or verify hypotheses by applying computational techniques to large scale network data. The highly experienced team of editors and high-profile authors from around the world present and explain a number of methods that are representative of computational network theory, derived from graph theory, as well as computational and statistical techniques. With its coherent structure and homogenous style, this reference is equally suitable for courses on computational networks.

Author : Matthias Dehmer
Publisher :
ISBN 13 : 9783527691517
Total Pages : pages
Book Rating : 4.10/5 ( download)

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Download or read book Computational Network Theory written by Matthias Dehmer and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : Matthias Dehmer
Publisher : John Wiley & Sons
ISBN 13 : 3527691545
Total Pages : 280 pages
Book Rating : 4.48/5 ( download)

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Download or read book Computational Network Theory written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2015-05-04 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive introduction to computational network theory as a branch of network theory builds on the understanding that such networks are a tool to derive or verify hypotheses by applying computational techniques to large scale network data. The highly experienced team of editors and high-profile authors from around the world present and explain a number of methods that are representative of computational network theory, derived from graph theory, as well as computational and statistical techniques. With its coherent structure and homogenous style, this reference is equally suitable for courses on computational networks.

Author : Gottfried Tinhofer
Publisher : Springer Science & Business Media
ISBN 13 : 3709190762
Total Pages : 282 pages
Book Rating : 4.60/5 ( download)

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Download or read book Computational Graph Theory written by Gottfried Tinhofer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: One ofthe most important aspects in research fields where mathematics is "applied is the construction of a formal model of a real system. As for structural relations, graphs have turned out to provide the most appropriate tool for setting up the mathematical model. This is certainly one of the reasons for the rapid expansion in graph theory during the last decades. Furthermore, in recent years it also became clear that the two disciplines of graph theory and computer science have very much in common, and that each one has been capable of assisting significantly in the development of the other. On one hand, graph theorists have found that many of their problems can be solved by the use of com puting techniques, and on the other hand, computer scientists have realized that many of their concepts, with which they have to deal, may be conveniently expressed in the lan guage of graph theory, and that standard results in graph theory are often very relevant to the solution of problems concerning them. As a consequence, a tremendous number of publications has appeared, dealing with graphtheoretical problems from a computational point of view or treating computational problems using graph theoretical concepts.

Author : Michael J. Kearns
Publisher : MIT Press
ISBN 13 : 9780262111935
Total Pages : 230 pages
Book Rating : 4.34/5 ( download)

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Download or read book An Introduction to Computational Learning Theory written by Michael J. Kearns and published by MIT Press. This book was released on 1994-08-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Emphasizing issues of computational efficiency, Michael Kearns and Umesh Vazirani introduce a number of central topics in computational learning theory for researchers and students in artificial intelligence, neural networks, theoretical computer science, and statistics. Computational learning theory is a new and rapidly expanding area of research that examines formal models of induction with the goals of discovering the common methods underlying efficient learning algorithms and identifying the computational impediments to learning. Each topic in the book has been chosen to elucidate a general principle, which is explored in a precise formal setting. Intuition has been emphasized in the presentation to make the material accessible to the nontheoretician while still providing precise arguments for the specialist. This balance is the result of new proofs of established theorems, and new presentations of the standard proofs. The topics covered include the motivation, definitions, and fundamental results, both positive and negative, for the widely studied L. G. Valiant model of Probably Approximately Correct Learning; Occam's Razor, which formalizes a relationship between learning and data compression; the Vapnik-Chervonenkis dimension; the equivalence of weak and strong learning; efficient learning in the presence of noise by the method of statistical queries; relationships between learning and cryptography, and the resulting computational limitations on efficient learning; reducibility between learning problems; and algorithms for learning finite automata from active experimentation.

Author : Petter Holme
Publisher : Springer Nature
ISBN 13 : 3031303997
Total Pages : 486 pages
Book Rating : 4.99/5 ( download)

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Download or read book Temporal Network Theory written by Petter Holme and published by Springer Nature. This book was released on 2023-11-20 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for epidemic modeling, optimization of transportation and logistics, as well as understanding biological phenomena. Over the past 20 years, network theory has proven to be one of the most powerful tools for studying and analyzing complex systems. Temporal network theory is perhaps the most recent significant development in the field in recent years, with direct applications to many of the “big data” sets. This book appeals to students, researchers, and professionals interested in theory and temporal networks—a field that has grown tremendously over the last decade. This second edition of Temporal Network Theory extends the first with three chapters highlighting recent developments in the interface with machine learning.

Author : Petter Holme
Publisher : Springer
ISBN 13 : 3642364616
Total Pages : 356 pages
Book Rating : 4.17/5 ( download)

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Download or read book Temporal Networks written by Petter Holme and published by Springer. This book was released on 2013-05-23 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: The concept of temporal networks is an extension of complex networks as a modeling framework to include information on when interactions between nodes happen. Many studies of the last decade examine how the static network structure affect dynamic systems on the network. In this traditional approach the temporal aspects are pre-encoded in the dynamic system model. Temporal-network methods, on the other hand, lift the temporal information from the level of system dynamics to the mathematical representation of the contact network itself. This framework becomes particularly useful for cases where there is a lot of structure and heterogeneity both in the timings of interaction events and the network topology. The advantage compared to common static network approaches is the ability to design more accurate models in order to explain and predict large-scale dynamic phenomena (such as, e.g., epidemic outbreaks and other spreading phenomena). On the other hand, temporal network methods are mathematically and conceptually more challenging. This book is intended as a first introduction and state-of-the art overview of this rapidly emerging field.

Author : Frank H.P. Fitzek
Publisher : Academic Press
ISBN 13 : 0128209046
Total Pages : 524 pages
Book Rating : 4.42/5 ( download)

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Download or read book Computing in Communication Networks written by Frank H.P. Fitzek and published by Academic Press. This book was released on 2020-05-20 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computing in Communication Networks: From Theory to Practice provides comprehensive details and practical implementation tactics on the novel concepts and enabling technologies at the core of the paradigm shift from store and forward (dumb) to compute and forward (intelligent) in future communication networks and systems. The book explains how to create virtualized large scale testbeds using well-established open source software, such as Mininet and Docker. It shows how and where to place disruptive techniques, such as machine learning, compressed sensing, or network coding in a newly built testbed. In addition, it presents a comprehensive overview of current standardization activities. Specific chapters explore upcoming communication networks that support verticals in transportation, industry, construction, agriculture, health care and energy grids, underlying concepts, such as network slicing and mobile edge cloud, enabling technologies, such as SDN/NFV/ ICN, disruptive innovations, such as network coding, compressed sensing and machine learning, how to build a virtualized network infrastructure testbed on one’s own computer, and more. Provides a uniquely comprehensive overview on the individual building blocks that comprise the concept of computing in future networks Gives practical hands-on activities to bridge theory and implementation Includes software and examples that are not only employed throughout the book, but also hosted on a dedicated website

Author : Petter Holme
Publisher : Springer Nature
ISBN 13 : 3030234959
Total Pages : 375 pages
Book Rating : 4.59/5 ( download)

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Download or read book Temporal Network Theory written by Petter Holme and published by Springer Nature. This book was released on 2019-10-29 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the theoretical side of temporal network research and gives an overview of the state of the art in the field. Curated by two pioneers in the field who have helped to shape it, the book contains contributions from many leading researchers. Temporal networks fill the border area between network science and time-series analysis and are relevant for the modeling of epidemics, optimization of transportation and logistics, as well as understanding biological phenomena. Network theory has proven, over the past 20 years to be one of the most powerful tools for the study and analysis of complex systems. Temporal network theory is perhaps the most recent significant development in the field in recent years, with direct applications to many of the "big data" sets. This monograph will appeal to students, researchers and professionals alike interested in theory and temporal networks, a field that has grown tremendously over the last decade.

Author : Matthias Dehmer
Publisher : John Wiley & Sons
ISBN 13 : 3527694404
Total Pages : 368 pages
Book Rating : 4.02/5 ( download)

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Download or read book Computational Network Analysis with R written by Matthias Dehmer and published by John Wiley & Sons. This book was released on 2016-07-22 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics. With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping. Written by editors and authors with an excellent track record in the field, this is the ultimate reference for R in Network Analysis.