Описание: This book explains synchronization and the implementation of concurrent objects, presenting synchronization algorithms while also introducing the theory that underlies the implementation of concurrent objects in the presence of asynchrony and process crashes.
Описание: Biology undergraduates, medical students and life-science graduate students often have limited mathematical skills. Similarly, physics, math and engineering students have little patience for the detailed facts that make up much of biological knowledge. Teaching computational neuroscience as an integrated discipline requires that both groups be brought forward onto common ground. This book does this by making ancillary material available in an appendix and providing basic explanations without becoming bogged down in unnecessary details. The book will be suitable for undergraduates and beginning graduate students taking a computational neuroscience course and also to anyone with an interest in the uses of the computer in modeling the nervous system.
Автор: Hanan Samet Название: Foundations of Multidimensional and Metric Data Structures, ISBN: 0123694469 ISBN-13(EAN): 9780123694461 Издательство: Elsevier Science Рейтинг: Цена: 10441.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Discusses multidimensional point data, object and image-based representations, intervals and small rectangles, and high-dimensional datasets. This book includes a comprehensive survey to spatial and multidimensional data structures and algorithms. It also includes implementation details for some of the most useful data structures.
Автор: Schapire Robert E., Freund Yoav Название: Boosting: Foundations and Algorithms ISBN: 0262017180 ISBN-13(EAN): 9780262017183 Издательство: MIT Press Рейтинг: Цена: 4037.00 р. Наличие на складе: Нет в наличии.
Описание:
Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate "rules of thumb." A remarkably rich theory has evolved around boosting, with connections to a range of topics, including statistics, game theory, convex optimization, and information geometry. Boosting algorithms have also enjoyed practical success in such fields as biology, vision, and speech processing. At various times in its history, boosting has been perceived as mysterious, controversial, even paradoxical.
This book, written by the inventors of the method, brings together, organizes, simplifies, and substantially extends two decades of research on boosting, presenting both theory and applications in a way that is accessible to readers from diverse backgrounds while also providing an authoritative reference for advanced researchers. With its introductory treatment of all material and its inclusion of exercises in every chapter, the book is appropriate for course use as well. The book begins with a general introduction to machine learning algorithms and their analysis; then explores the core theory of boosting, especially its ability to generalize; examines some of the myriad other theoretical viewpoints that help to explain and understand boosting; provides practical extensions of boosting for more complex learning problems; and finally presents a number of advanced theoretical topics. Numerous applications and practical illustrations are offered throughout.
Автор: Manning, Christopher D. Schutze, Hinrich Название: Foundations of statistical natural language processing ISBN: 0262133601 ISBN-13(EAN): 9780262133609 Издательство: MIT Press Рейтинг: Цена: 19468.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Statistical approaches to processing natural language text have become dominant in recent years. This foundational text is the first comprehensive introduction to statistical natural language processing (NLP) to appear. The book contains all the theory and algorithms needed for building NLP tools. It provides broad but rigorous coverage of mathematical and linguistic foundations, as well as detailed discussion of statistical methods, allowing students and researchers to construct their own implementations. The book covers collocation finding, word sense disambiguation, probabilistic parsing, information retrieval, and other applications.
Автор: Osamu Watanabe; Thomas Zeugmann Название: Stochastic Algorithms: Foundations and Applications ISBN: 3642049435 ISBN-13(EAN): 9783642049439 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 5th International Symposium on Stochastic Algorithms, Foundations and Applications, SAGA 2009, held in Sapporo, Japan, in October 2009. The 15 revised full papers presented together with 2 invited papers were carefully reviewed and selected from 22 submissions.
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