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Handbook on neural information processing

Author: Monica Bianchini; Marco Maggini; L C Jain
Publisher: Berlin ; New York : Springer, ©2013.
Series: Intelligent systems reference library, 49.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: Deep architectures Recurrent, recursive, and graph neural networks Cellular neural networks Bayesian networks Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for  Read more...
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Genre/Form: Electronic books
Ebook
Handbooks and manuals
Handbooks, manuals, etc
Additional Physical Format: Print version:
Handbook on neural information processing.
Berlin ; New York : Springer, ©2013
(DLC) 2013932221
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Monica Bianchini; Marco Maggini; L C Jain
ISBN: 9783642366574 3642366570
OCLC Number: 840604176
Description: 1 online resource.
Contents: Deep Learning of Representations / Yoshua Bengio, Aaron Courville --
Recurrent Neural Networks / Sajid A. Marhon, Christopher J.F. Cameron --
Supervised Neural Network Models for Processing Graphs / Monica Bianchini, Marco Maggini --
Topics on Cellular Neural Networks / Liviu Goraş, Ion Vornicu, Paul Ungureanu --
Approximating Multivariable Functions by Feedforward Neural Nets / Paul C. Kainen, Věra Kůrková --
Bochner Integrals and Neural Networks / Paul C. Kainen, Andrew Vogt --
Semi-supervised Learning / Mohamed Farouk Abdel Hady, Friedhelm Schwenker --
Statistical Relational Learning / Hendrik Blockeel --
Kernel Methods for Structured Data / Andrea Passerini --
Multiple Classifier Systems: Theory, Applications and Tools / Francesco Gargiulo, Claudio Mazzariello --
Self Organisation and Modal Learning: Algorithms and Applications / Dominic Palmer-Brown, Chrisina Jayne --
Bayesian Networks, Introduction and Practical Applications / Wim Wiegerinck, Willem Burgers, Bert Kappen --
Relevance Feedback in Content-Based Image Retrieval: A Survey / Jing Li, Nigel M. Allinson --
Learning Structural Representations of Text Documents in Large Document Collections / Ah Chung Tsoi, Markus Hagenbuchner, Milly Kc --
Neural Networks in Bioinformatics / Masood Zamani, Stefan C. Kremer.
Series Title: Intelligent systems reference library, 49.
Responsibility: Monica Bianchini, Marco Maggini, and Lakhmi C. Jain (eds.).

Abstract:

This handbook presents some of the most recent topics in neural information processing, covering both theoretical concepts and practical applications. The contributions include: Deep architectures Recurrent, recursive, and graph neural networks Cellular neural networks Bayesian networks Approximation capabilities of neural networks Semi-supervised learning Statistical relational learning Kernel methods for structured data Multiple classifier systems Self organisation and modal learning Applications to content-based image retrieval, text mining in large document collections, and bioinformat.

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