Автор: David J. C. MacKay Название: Information Theory, Inference and Learning Algorithms ISBN: 0521642981 ISBN-13(EAN): 9780521642989 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This exciting and entertaining textbook is ideal for courses in information, communication and coding. It is an unparalleled entry point to these subjects for professionals working in areas as diverse as computational biology, data mining, financial engineering and machine learning.
Автор: Sung Название: Algorithms in Bioinformatics ISBN: 1420070339 ISBN-13(EAN): 9781420070330 Издательство: Taylor&Francis Рейтинг: Цена: 13779.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents an introduction to the algorithmic techniques applied in bioinformatics. For each topic, this title details the biological motivation, defines the corresponding computational problems, and includes examples to illustrate each algorithm.
Автор: Cormen, Thomas H., E Название: Introduction to algorithms 3 ed. ISBN: 0262033844 ISBN-13(EAN): 9780262033848 Издательство: MIT Press Рейтинг: Цена: 27588.00 р. Наличие на складе: Нет в наличии.
Описание: A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-base flow.
Автор: Niedermeier, Rolf Название: Invitation to fixed-parameter algorithms ISBN: 0198566077 ISBN-13(EAN): 9780198566076 Издательство: Oxford Academ Рейтинг: Цена: 21780.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An application-oriented introduction to the highly topical area of the development and analysis of efficient fixed-parameter algorithms for hard problems. Aimed at graduate and research mathematicians, algorithm designers, and computer scientists, it provides a fresh view on this highly innovative field of algorithmic research.
Автор: Donald Bruce R. Название: Algorithms in Structural Molecular Biology ISBN: 0262015595 ISBN-13(EAN): 9780262015592 Издательство: MIT Press Рейтинг: Цена: 11850.00 р. Наличие на складе: Нет в наличии.
Описание:
An overview of algorithms important to computational structural biology that addresses such topics as NMR and design and analysis of proteins.
Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering. This book explains the algorithmic foundations and computational approaches underlying areas of structural biology including NMR (nuclear magnetic resonance); X-ray crystallography; and the design and analysis of proteins, peptides, and small molecules.
Each chapter offers a concise overview of important concepts, focusing on a key topic in the field. Four chapters offer a short course in algorithmic and computational issues related to NMR structural biology, giving the reader a useful toolkit with which to approach the fascinating yet thorny computational problems in this area. A recurrent theme is understanding the interplay between biophysical experiments and computational algorithms. The text emphasizes the mathematical foundations of structural biology while maintaining a balance between algorithms and a nuanced understanding of experimental data. Three emerging areas, particularly fertile ground for research students, are highlighted: NMR methodology, design of proteins and other molecules, and the modeling of protein flexibility.
The next generation of computational structural biologists will need training in geometric algorithms, provably good approximation algorithms, scientific computation, and an array of techniques for handling noise and uncertainty in combinatorial geometry and computational biophysics. This book is an essential guide for young scientists on their way to research success in this exciting field.
Автор: Edelsbrunner Herbert Название: Algorithms in Combinatorial Geometry ISBN: 3642648738 ISBN-13(EAN): 9783642648731 Издательство: Springer Цена: 18161.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.
Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.
After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.
Автор: Nancy A. Lynch Название: Distributed Algorithms, ISBN: 1558603484 ISBN-13(EAN): 9781558603486 Издательство: Elsevier Science Рейтинг: Цена: 20549.00 р. Наличие на складе: Нет в наличии.
Описание: A guide to designing, implementing and analyzing distributed algorithms. It covers problems including resource allocation, communication, consensus among distributed processes, data consistency, deadlock detection, leader election and global snapshots.
Автор: Mukhopadhyay Sambit, Morris Edward, Arulkumaran Sa Название: Algorithms for Obstetrics and Gynaecology ISBN: 0199651396 ISBN-13(EAN): 9780199651399 Издательство: Oxford Academ Рейтинг: Цена: 8129.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Algorithms in Obstetrics and Gynaecology presents the core knowledge needed to tackle all situations in obstetrics and gynaecology, in a structured fashion. All algorithms are designed to support rapid decision making in the most clinically relevant situations to minimise the risks of a poor outcome.
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.
Автор: Parker J J Название: Algorithms for Image Processing and Computer Vision ISBN: 0470643854 ISBN-13(EAN): 9780470643853 Издательство: Wiley Рейтинг: Цена: 12514.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Programmers, scientists, and engineers are always in need of newer techniques and algorithms to manipulate and interpret images. Algorithms for Image Processing and Computer Vision is an accessible collection of algorithms for common image processing applications that simplifies complicated mathematical calculations.
Описание: The material covered by this book has been taught by one of the authors in a post-graduate course on Numerical Analysis at the University Pierre et Marie Curie of Paris. It is an extended version of a previous text (cf. Girault & Raviart [32J) published in 1979 by Springer-Verlag in its series: Lecture Notes in Mathematics.
In the last decade, many engineers and mathematicians have concentrated their efforts on the finite element solution of the Navier-Stokes equations for incompressible flows. The purpose of this book is to provide a fairly comprehen- sive treatment of the most recent developments in that field. To stay within reasonable bounds, we have restricted ourselves to the case of stationary prob- lems although the time-dependent problems are of fundamental importance.
This topic is currently evolving rapidly and we feel that it deserves to be covered by another specialized monograph. We have tried, to the best of our ability, to present a fairly exhaustive treatment of the finite element methods for inner flows. On the other hand however, we have entirely left out the subject of exterior problems which involve radically different techniques, both from a theoretical and from a practical point of view.
Also, we have neither discussed the implemen- tation of the finite element methods presented by this book, nor given any explicit numerical result. This field is extensively covered by Peyret & Taylor [64J and Thomasset [82].
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