Bianchini / Maggini / Jain Handbook on Neural Information Processing

2013
ISBN: 978-3-642-36657-4
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 49, 538 Seiten, eBook

Reihe: Intelligent Systems Reference Library

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.

Zielgruppe

Research

Autoren/Hrsg.

Bianchini, Monica

Maggini, Marco

Jain, Lakhmi C.

Inhaltsverzeichnis

Neural Network Architectures.- Learning paradigms.- Reasoning and applications.- conclusions. Reasoning and applications.- conclusions. Reasoning and applications.- conclusions.