Handbook on Neural Information Processing

Handbook on Neural Information Processing
ISBN-10
3642366570
ISBN-13
9783642366574
Category
Technology & Engineering
Pages
538
Language
English
Published
2013-04-12
Publisher
Springer Science & Business Media
Authors
Lakhmi C. Jain, Monica Bianchini, Marco Maggini

Description

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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