Handbook on Neural Information Processing
1st Edition
Published on 12. April 2013
XX, 538 pages
978-3-642-36657-4 (ISBN)
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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Other editions
Additional editions
Monica Bianchini | Marco Maggini | Lakhmi C. Jain
Handbook on Neural Information Processing
Book
05/2015
Springer
€160.49
Shipment within 7-9 days
Monica Bianchini | Marco Maggini | Lakhmi C. Jain
Handbook on Neural Information Processing
Book
04/2013
Springer
€160.49
Shipment within 7-9 days
Content
Neural Network Architectures.- Learning paradigms.- Reasoning and applications.- conclusions. Reasoning and applications.- conclusions. Reasoning and applications.- conclusions.
