Handbook on Neural Information Processing

2013
ISBN: 978-3-642-36656-7
Verlag: Springer

Buch, Englisch, Band 49, 538 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 9575 g

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

Jain, Lakhmi C.

Maggini, Marco

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Neuronale Netzwerke

Inhaltsverzeichnis

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

Reasoning and applications.- conclusions.

Reasoning and applications.- conclusions.