Deep learning on graphs, Ma, Yao (michigan State University) Tang, Jiliang (michigan State University)
Автор: Goodfellow Ian, Bengio Yoshua, Courville Aaron Название: Deep Learning ISBN: 0262035618 ISBN-13(EAN): 9780262035613 Издательство: MIT Press Рейтинг: Цена: 13543.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.
"Written by three experts in the field, Deep Learning is the only comprehensive book on the subject." -- Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.
The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.
Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Автор: Bollobas, Bela Название: Random graphs ISBN: 0521797225 ISBN-13(EAN): 9780521797221 Издательство: Cambridge Academ Рейтинг: Цена: 13306.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: In this second edition of a now classic text, the addition of two new sections, numerous new results and over 150 references mean that this represents a comprehensive account of random graph theory. Suitable for mathematicians, computer scientists and electrical engineers, as well as people working in biomathematics.
Описание: Since its inception in the 1960s, the theory of random graphs has evolved into a dynamic branch of discrete mathematics. Yet despite the lively activity and important applications, the last comprehensive volume on the subject is Bollobas`s well-known 1985 book.
Автор: Philipp Blanchard; Dimitri Volchenkov Название: Random Walks and Diffusions on Graphs and Databases ISBN: 3642268420 ISBN-13(EAN): 9783642268427 Издательство: Springer Рейтинг: Цена: 12571.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces the theory of graphs and random walks on graphs, covers methods for exploring the structure of finite connected graphs and databases, and details applications in electric resistance networks, urban planning, linguistic databases and more.
Автор: Jakob Jonsson Название: Simplicial Complexes of Graphs ISBN: 3540758585 ISBN-13(EAN): 9783540758587 Издательство: Springer Рейтинг: Цена: 7959.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A graph complex is a finite family of graphs closed under deletion of edges. Identifying each graph with its edge set, one may view a graph complex as a simplicial complex and hence interpret it as a geometric object. This volume examines topological properties of graph complexes, focusing on homotopy type and homology.
Автор: Erhard Godehardt Название: Graphs as Structural Models ISBN: 3528063122 ISBN-13(EAN): 9783528063122 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The advent of the high-speed computer with its enormous storage capabilities enabled statisticians as well as researchers from the different topics of life sciences to apply mul- tivariate statistical procedures to large data sets to explore their structures.
Автор: Alison M. Marr; W.D. Wallis Название: Magic Graphs ISBN: 1489996281 ISBN-13(EAN): 9781489996282 Издательство: Springer Рейтинг: Цена: 6981.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This concise, self-contained exposition is unique in its focus on the theory of magic graphs/labelings and its application to a number of new areas. It may serve as a graduate text for courses and seminars in mathematics or computer science, or as a professional text for the researcher.
Автор: Coolen A.C.C. Название: Generating Random Networks and Graphs ISBN: 0198709897 ISBN-13(EAN): 9780198709893 Издательство: Oxford Academ Рейтинг: Цена: 11880.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book describes how to correctly and efficiently generate random networks based on certain constraints. Being able to test a hypothesis against a properly specified control case is at the heart of the `scientific method`.
Автор: Kocay William Название: Graphs, Algorithms, and Optimization ISBN: 1482251167 ISBN-13(EAN): 9781482251166 Издательство: Taylor&Francis Рейтинг: Цена: 12554.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The second edition of this popular book presents the theory of graphs from an algorithmic viewpoint. The authors present the graph theory in a rigorous, but informal style and cover most of the main areas of graph theory. The ideas of surface topology are presented from an intuitive point of view. We have also included a discussion on linear programming that emphasizes problems in graph theory. The text is suitable for students in computer science or mathematics programs.
Автор: Chartrand Gary Название: Graphs & Digraphs ISBN: 1498735762 ISBN-13(EAN): 9781498735766 Издательство: Taylor&Francis Рейтинг: Цена: 16078.00 р. Наличие на складе: Нет в наличии.
Описание:
Graphs & Digraphs masterfully employs student-friendly exposition, clear proofs, abundant examples, and numerous exercises to provide an essential understanding of the concepts, theorems, history, and applications of graph theory.
Fully updated and thoughtfully reorganized to make reading and locating material easier for instructors and students, the Sixth Edition of this bestselling, classroom-tested text:
Adds more than 160 new exercises
Presents many new concepts, theorems, and examples
Includes recent major contributions to long-standing conjectures such as the Hamiltonian Factorization Conjecture, 1-Factorization Conjecture, and Alspach's Conjecture on graph decompositions
Supplies a proof of the perfect graph theorem
Features a revised chapter on the probabilistic method in graph theory with many results integrated throughout the text
At the end of the book are indices and lists of mathematicians' names, terms, symbols, and useful references. There is also a section giving hints and solutions to all odd-numbered exercises. A complete solutions manual is available with qualifying course adoption.
Graphs & Digraphs, Sixth Edition remains the consummate text for an advanced undergraduate level or introductory graduate level course or two-semester sequence on graph theory, exploring the subject's fascinating history while covering a host of interesting problems and diverse applications.
Автор: Martin T. Barlow; Gordon Slade Название: Random Graphs, Phase Transitions, and the Gaussian Free Field ISBN: 3030320103 ISBN-13(EAN): 9783030320102 Издательство: Springer Рейтинг: Цена: 25155.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The 2017 PIMS-CRM Summer School in Probability was held at the Pacific Institute for the Mathematical Sciences (PIMS) at the University of British Columbia in Vancouver, Canada, during June 5-30, 2017. It had 125 participants from 20 different countries, and featured two main courses, three mini-courses, and twenty-nine lectures.The lecture notes contained in this volume provide introductory accounts of three of the most active and fascinating areas of research in modern probability theory, especially designed for graduate students entering research: Scaling limits of random trees and random graphs (Christina Goldschmidt)Lectures on the Ising and Potts models on the hypercubic lattice (Hugo Duminil-Copin)Extrema of the two-dimensional discrete Gaussian free field (Marek Biskup) Each of these contributions provides a thorough introduction that will be of value to beginners and experts alike.
Описание: This book provides readers with a practical guide to the principles of hybrid approaches to natural language processing (NLP) involving a combination of neural methods and knowledge graphs.
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