Data Analysis of Asymmetric Structures, Saito, Takayuki , Yadohisa, Hiroshi

Автор: Fred J. Hickernell, Peter Kritzer
Название: Multivariate Algorithms and Information-Based Complexity
ISBN: 3110633116 ISBN-13(EAN): 9783110633115
Издательство: Walter de Gruyter
Цена: 19330.00 р.
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Описание:

The series is devoted to the publication of high-level monographs, surveys and proceedings which cover the whole spectrum of computational and applied mathematics.

Автор: Garban
Название: Noise Sensitivity of Boolean Functions and Percolation
ISBN: 1107432553 ISBN-13(EAN): 9781107432550
Издательство: Cambridge Academ
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Цена: 6019.00 р.
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Описание: This account of the new and exciting area of noise sensitivity of Boolean functions - in particular applied to critical percolation - is designed for graduate students and researchers in probability theory, discrete mathematics, and theoretical computer science. It assumes a basic background in probability theory and integration theory. Each chapter ends with exercises.

Автор: Berthold Lausen; Sabine Krolak-Schwerdt; Matthias
Название: Data Science, Learning by Latent Structures, and Knowledge Discovery
ISBN: 366244982X ISBN-13(EAN): 9783662449820
Издательство: Springer
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Цена: 18167.00 р.
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Описание: This volume comprises papers dedicated to data science and the extraction of knowledge from many types of data: structural, quantitative, or statistical approaches for the analysis of data;

Автор: Hofstad
Название: Random Graphs and Complex Networks
ISBN: 110717287X ISBN-13(EAN): 9781107172876
Издательство: Cambridge Academ
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Цена: 8237.00 р.
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Описание: Network science is one of the fastest growing areas in science and business. This classroom-tested, self-contained book is designed for master`s-level courses and provides a rigorous treatment of random graph models for networks, featuring many examples of real-world networks for motivation and numerous exercises to build intuition and experience.

Автор: Sigbert Klinke
Название: Data Structures for Computational Statistics
ISBN: 3790809829 ISBN-13(EAN): 9783790809824
Издательство: Springer
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Цена: 19564.00 р.
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Описание: Since the beginning of the seventies computer hardware is available to use programmable computers for various tasks. The introduction of personal computers in the eighties gave new impulses for even further development, already at the beginning of the seven- ties some special languages like SAS or SPSS were available for statisticians.

Автор: Mitzenmacher
Название: Probability and Computing
ISBN: 110715488X ISBN-13(EAN): 9781107154889
Издательство: Cambridge Academ
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Цена: 8237.00 р.
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Описание: This greatly expanded new edition, requiring only an elementary background in discrete mathematics, comprehensively covers randomization and probabilistic techniques in modern computer science. It includes new material relevant to machine learning and big data analysis, plus examples and exercises, enabling students to learn modern techniques and applications.

Автор: Claudia Becker; Roland Fried; Sonja Kuhnt
Название: Robustness and Complex Data Structures
ISBN: 3642354939 ISBN-13(EAN): 9783642354939
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Presented in honor of Ursula Gather`s 60th birthday this book deals with modern topics in the field of robust statistical methods, especially for time series and regression analysis, and with statistical methods for complex data structures.

Автор: Moitra, Ankur (massachusetts Institute Of Technology)
Название: Algorithmic aspects of machine learning
ISBN: 1107184584 ISBN-13(EAN): 9781107184589
Издательство: Cambridge Academ
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Цена: 10613.00 р.
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Описание: Machine learning is reshaping our everyday life. This book explores the theoretical underpinnings in an accessible way, offering theoretical computer scientists an introduction to important models and problems and offering machine learning researchers a cutting-edge algorithmic toolkit.

Автор: Moitra Ankur
Название: Algorithmic Aspects of Machine Learning
ISBN: 1316636003 ISBN-13(EAN): 9781316636008
Издательство: Cambridge Academ
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Цена: 5386.00 р.
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Описание: Machine learning is reshaping our everyday life. This book explores the theoretical underpinnings in an accessible way, offering theoretical computer scientists an introduction to important models and problems and offering machine learning researchers a cutting-edge algorithmic toolkit.

Автор: Claudia Becker; Roland Fried; Sonja Kuhnt
Название: Robustness and Complex Data Structures
ISBN: 3642443869 ISBN-13(EAN): 9783642443862
Издательство: Springer
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Цена: 15372.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Presented in honor of Ursula Gather`s 60th birthday this book deals with modern topics in the field of robust statistical methods, especially for time series and regression analysis, and with statistical methods for complex data structures.