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Handbook on Neural Information Processing

by Bianchini, Monica.
Authors: Maggini, Marco.%editor. | Jain, Lakhmi C.%editor. | SpringerLink (Online service) Series: Intelligent Systems Reference Library, 1868-4394 ; . 49 Physical details: XX, 538 p. 144 illus. online resource. ISBN: 3642366570 Subject(s): Engineering. | Artificial intelligence. | Engineering. | Computational Intelligence. | Artificial Intelligence (incl. Robotics).
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Neural Network Architectures -- Learning paradigms -- Reasoning and applications -- conclusions. Reasoning and applications -- conclusions. Reasoning and applications -- conclusions.

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 bioinformatics   This book is thought particularly for graduate students, researchers and practitioners, willing to deepen their knowledge on more advanced connectionist models and related learning paradigms.

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