Models, Algorithms and Technologies for Network Analysis, Mikhail V. Batsyn; Valery A. Kalyagin; Panos M. Pa
Автор: Kalyagin Название: Models, Algorithms and Technologies for Network Analysis ISBN: 331929606X ISBN-13(EAN): 9783319296067 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The contributions in this volume cover a broad range of topics including maximum cliques, graph coloring, data mining, brain networks, Steiner forest, logistic and supply chain networks. Network algorithms and their applications to market graphs, manufacturing problems, internet networks and social networks are highlighted. The 'Fourth International Conference in Network Analysis,' held at the Higher School of Economics, Nizhny Novgorod in May 2014, initiated joint research between scientists, engineers and researchers from academia, industry and government; the major results of conference participants have been reviewed and collected in this Work. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis.
Автор: Valery A. Kalyagin; Alexey I. Nikolaev; Panos M. P Название: Models, Algorithms, and Technologies for Network Analysis ISBN: 3319568280 ISBN-13(EAN): 9783319568287 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Mikhail V. Batsyn; Valery A. Kalyagin; Panos M. Pa Название: Models, Algorithms and Technologies for Network Analysis ISBN: 3319343521 ISBN-13(EAN): 9783319343525 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume compiles the major results of conference participants from the "Third International Conference in Network Analysis" held at the Higher School of Economics, Nizhny Novgorod in May 2013, with the aim to initiate further joint research among different groups.
Автор: Asmussen Название: Stochastic Simulation: Algorithms and Analysis ISBN: 038730679X ISBN-13(EAN): 9780387306797 Издательство: Springer Рейтинг: Цена: 6981.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines. This book provides a broad treatment of such sampling-based methods , as well as accompanying mathematical analysis of the convergence properties of the methods discussed . The reach of the ideas is illustrated by discussing a wide range of applications and the models that have found wide usage. The first half of the book focusses on general methods, whereas the second half discusses model-specific algorithms. Given the wide range of examples, exercises and applications students, practitioners and researchers in probability, statistics, operations research, economics, finance, engineering as well as biology and chemistry and physics will find the book of value. Soren Asmussen is Professor of Applied Probability at Aarhus University, Denmark and Peter Glynn is Thomas Ford Professor of Engineering at Stanford University.
Название: Advances in Computational Algorithms and Data Analysis ISBN: 140208918X ISBN-13(EAN): 9781402089183 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Advances in Computational Algorithms and Data Analysis offers state of the art tremendous advances in computational algorithms and data analysis. The volume serves as an excellent reference work for researchers and graduate students working on computational algorithms and data analysis.
Название: Practical Analysis of Algorithms ISBN: 331909887X ISBN-13(EAN): 9783319098876 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts.
Автор: Alsuwaiyel M H Название: Algorithms: Design Techniques And Analysis (Revised Edition) ISBN: 9814723649 ISBN-13(EAN): 9789814723640 Издательство: World Scientific Publishing Рейтинг: Цена: 22810.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Problem solving is an essential part of every scientific discipline. It has two components: (1) problem identification and formulation, and (2) the solution to the formulated problem. One can solve a problem on its own using ad hoc techniques or by following techniques that have produced efficient solutions to similar problems. This requires the understanding of various algorithm design techniques, how and when to use them to formulate solutions, and the context appropriate for each of them.Algorithms: Design Techniques and Analysis advocates the study of algorithm design by presenting the most useful techniques and illustrating them with numerous examples — emphasizing on design techniques in problem solving rather than algorithms topics like searching and sorting. Algorithmic analysis in connection with example algorithms are explored in detail. Each technique or strategy is covered in its own chapter through numerous examples of problems and their algorithms.Readers will be equipped with problem solving tools needed in advanced courses or research in science and engineering.
Описание: This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc.
Автор: Roberto Tempo; Giuseppe Calafiore; Fabrizio Dabben Название: Randomized Algorithms for Analysis and Control of Uncertain Systems ISBN: 1447146093 ISBN-13(EAN): 9781447146094 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces readers to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. It provides tools for dealing with uncertainty in control systems.
Автор: Thomas Bartz-Beielstein; Marco Chiarandini; Lu?s P Название: Experimental Methods for the Analysis of Optimization Algorithms ISBN: 364244590X ISBN-13(EAN): 9783642445903 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With contributions from leaders in the field, this volume assesses the main issues in the experimental analysis of algorithms, examines their developmental cycle, and demonstrates how to configure and tune algorithms with advanced experimental techniques.
Автор: Roberto Tempo; Giuseppe Calafiore; Fabrizio Dabben Название: Randomized Algorithms for Analysis and Control of Uncertain Systems ISBN: 1447161408 ISBN-13(EAN): 9781447161400 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces readers to the fundamentals of probabilistic methods in the analysis and design of systems subject to deterministic and stochastic uncertainty. It provides tools for dealing with uncertainty in control systems.
Автор: Slawomir Wierzcho?; Mieczyslaw A. K?opotek Название: Modern Algorithms of Cluster Analysis ISBN: 3319693077 ISBN-13(EAN): 9783319693071 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides the reader with a basic understanding of the formal concepts of the cluster, clustering, partition, cluster analysis etc. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences. Understanding the related formal concepts is particularly vital in the epoch of Big Data; due to the volume and characteristics of the data, it is no longer feasible to predominantly rely on merely viewing the data when facing a clustering problem. Usually clustering involves choosing similar objects and grouping them together. To facilitate the choice of similarity measures for complex and big data, various measures of object similarity, based on quantitative (like numerical measurement results) and qualitative features (like text), as well as combinations of the two, are described, as well as graph-based similarity measures for (hyper) linked objects and measures for multilayered graphs. Numerous variants demonstrating how such similarity measures can be exploited when defining clustering cost functions are also presented. In addition, the book provides an overview of approaches to handling large collections of objects in a reasonable time. In particular, it addresses grid-based methods, sampling methods, parallelization via Map-Reduce, usage of tree-structures, random projections and various heuristic approaches, especially those used for community detection.
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