Artificial Neural Networks and Machine Learning – ICANN 2017, Alessandra Lintas; Stefano Rovetta; Paul F.M.J. Ve
Автор: Kevin Murphy Название: Machine Learning ISBN: 0262018020 ISBN-13(EAN): 9780262018029 Издательство: MIT Press Рейтинг: Цена: 124150.00 T Наличие на складе: Невозможна поставка. Описание:
A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.
The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package -- PMTK (probabilistic modeling toolkit) -- that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.
Автор: Gerhard Wei? Название: Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments ISBN: 3540629343 ISBN-13(EAN): 9783540629344 Издательство: Springer Рейтинг: Цена: 65210.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This report documents current and ongoing developments in the area of learning in distributed artificial intelligence systems. The interdisciplinary co-operation of researchers from DAI and machine learning has established an active area of research and development.
Автор: Petia Koprinkova-Hristova; Valeri Mladenov; Nikola Название: Artificial Neural Networks ISBN: 3319099027 ISBN-13(EAN): 9783319099026 Издательство: Springer Рейтинг: Цена: 232910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
The book reports on the latest theories on artificial neural networks, with a special emphasis on bio-neuroinformatics methods. It includes twenty-three papers selected from among the best contributions on bio-neuroinformatics-related issues, which were presented at the International Conference on Artificial Neural Networks, held in Sofia, Bulgaria, on September 10-13, 2013 (ICANN 2013). The book covers a broad range of topics concerning the theory and applications of artificial neural networks, including recurrent neural networks, super-Turing computation and reservoir computing, double-layer vector perceptrons, nonnegative matrix factorization, bio-inspired models of cell communities, Gestalt laws, embodied theory of language understanding, saccadic gaze shifts and memory formation, and new training algorithms for Deep Boltzmann Machines, as well as dynamic neural networks and kernel machines. It also reports on new approaches to reinforcement learning, optimal control of discrete time-delay systems, new algorithms for prototype selection, and group structure discovering. Moreover, the book discusses one-class support vector machines for pattern recognition, handwritten digit recognition, time series forecasting and classification, and anomaly identification in data analytics and automated data analysis. By presenting the state-of-the-art and discussing the current challenges in the fields of artificial neural networks, bioinformatics and neuroinformatics, the book is intended to promote the implementation of new methods and improvement of existing ones, and to support advanced students, researchers and professionals in their daily efforts to identify, understand and solve a number of open questions in these fields.
Автор: Johan A.K. Suykens; Joos P.L. Vandewalle; B.L. de Название: Artificial Neural Networks for Modelling and Control of Non-Linear Systems ISBN: 0792396782 ISBN-13(EAN): 9780792396789 Издательство: Springer Рейтинг: Цена: 156720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems.
Автор: Bert Kappen; Stan Gielen Название: Neural Networks: Artificial Intelligence and Industrial Applications ISBN: 3540199926 ISBN-13(EAN): 9783540199922 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume contains papers presented at the Third Annual SNN Symposium on Neural Networks held in Nijmegen, 1995. It summarizes developments in neurobiology, the cognitive sciences, robotics, and vision and data modelling. Working neural network solutions to industrial problems are also presented.
Автор: Gerard Chollet; Maria-Gabriella Di Benedetto; Anna Название: Speech Processing, Recognition and Artificial Neural Networks ISBN: 1852330945 ISBN-13(EAN): 9781852330941 Издательство: Springer Рейтинг: Цена: 139310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Speech Processing, Recognition and Artificial Neural Networks contains papers from leading researchers and selected students, discussing the experiments, theories and perspectives of acoustic phonetics as well as the latest techniques in the field of spe ech science and technology. Auditory and Neural Network Models for Speech;
Автор: David J. Livingstone Название: Artificial Neural Networks ISBN: 1617377384 ISBN-13(EAN): 9781617377389 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this book, international experts report the history of the application of ANN to chemical and biological problems, provide a guide to network architectures, training and the extraction of rules from trained networks, and cover many cutting-edge examples of the application of ANN to chemistry and biology.
Автор: H. Malmgren; M. Borga; L. Niklasson Название: Artificial Neural Networks in Medicine and Biology ISBN: 1852332891 ISBN-13(EAN): 9781852332891 Издательство: Springer Рейтинг: Цена: 153720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume comprises a selection of papers focusing specifically on the topics of ANNs in medicine and biology. It covers three main areas: the medical applications of ANNs, such as in diagnosis and outcome prediction, medical image analysis, and medical signal processing.
Автор: Sied Mehdi Fakhraie; Kenneth C. Smith Название: VLSI — Compatible Implementations for Artificial Neural Networks ISBN: 0792398254 ISBN-13(EAN): 9780792398257 Издательство: Springer Рейтинг: Цена: 158380.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Introduces an approach to biologically-inspired and VLSI-compatible definition, simulation, and implementation of artificial neural networks. This book develops a set of guidelines for general hardware implementation of artificial neural networks. It provides a geometrical interpretation of the behavior of different variants of these networks.
Автор: Stan Gielen; Bert Kappen Название: ICANN `93 ISBN: 3540198393 ISBN-13(EAN): 9783540198390 Издательство: Springer Рейтинг: Цена: 81050.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: A survey of current research in the field of neural networks, which describes computerized models of higher order human brain functions, the relationship between neural network architecture and function, and the need to extract computational principles from neurobiological findings.
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: Stefan Wermter; Cornelius Weber; Wlodzislaw Duch; Название: Artificial Neural Networks and Machine Learning -- ICANN 2014 ISBN: 3319111787 ISBN-13(EAN): 9783319111780 Издательство: Springer Рейтинг: Цена: 89440.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book constitutes the proceedings of the 24th International Conference on Artificial Neural Networks, ICANN 2014, held in Hamburg, Germany, in September 2014. The 107 papers included in the proceedings were carefully reviewed and selected from 173 submissions. The focus of the papers is on following topics: recurrent networks;
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