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Introduction To The Theory Of Neural Computation

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Release : 2018-03-08
Genre : Science
Kind : eBook
Book Rating : 213/5 ( reviews)

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Book Synopsis Introduction To The Theory Of Neural Computation by : John A. Hertz

Download or read book Introduction To The Theory Of Neural Computation written by John A. Hertz. This book was released on 2018-03-08. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.

Unsupervised Learning

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Release : 1999-05-24
Genre : Medical
Kind : eBook
Book Rating : 684/5 ( reviews)

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Book Synopsis Unsupervised Learning by : Geoffrey Hinton

Download or read book Unsupervised Learning written by Geoffrey Hinton. This book was released on 1999-05-24. Available in PDF, EPUB and Kindle. Book excerpt: Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.

Handbook of Neural Computation

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Release : 2017-07-18
Genre : Technology & Engineering
Kind : eBook
Book Rating : 197/5 ( reviews)

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Book Synopsis Handbook of Neural Computation by : Pijush Samui

Download or read book Handbook of Neural Computation written by Pijush Samui. This book was released on 2017-07-18. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Neural Computation and Self-organizing Maps

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Author :
Release : 1992
Genre : Computers
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Neural Computation and Self-organizing Maps by : Helge Ritter

Download or read book Neural Computation and Self-organizing Maps written by Helge Ritter. This book was released on 1992. Available in PDF, EPUB and Kindle. Book excerpt:

Graphical Models

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Release : 2001
Genre : Artificial intelligence
Kind : eBook
Book Rating : 422/5 ( reviews)

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Book Synopsis Graphical Models by : Michael Irwin Jordan

Download or read book Graphical Models written by Michael Irwin Jordan. This book was released on 2001. Available in PDF, EPUB and Kindle. Book excerpt: This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithm and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Graphical models use graphs to represent and manipulate joint probability distributions. They have their roots in artificial intelligence, statistics, and neural networks. The clean mathematical formalism of the graphical models framework makes it possible to understand a wide variety of network-based approaches to computation, and in particular to understand many neural network algorithms and architectures as instances of a broader probabilistic methodology. It also makes it possible to identify novel features of neural network algorithms and architectures and to extend them to more general graphical models.This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithms and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Contributors H. Attias, C. M. Bishop, B. J. Frey, Z. Ghahramani, D. Heckerman, G. E. Hinton, R. Hofmann, R. A. Jacobs, Michael I. Jordan, H. J. Kappen, A. Krogh, R. Neal, S. K. Riis, F. B. Rodríguez, L. K. Saul, Terrence J. Sejnowski, P. Smyth, M. E. Tipping, V. Tresp, Y. Weiss

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