Description
Handbook on Neural Information Processing, 2013
Intelligent Systems Reference Library Series, Vol. 49
Coordinators: Bianchini Monica, Maggini Marco, Jain Lakhmi C.
Language: EnglishPublication date: 05-2015
Support: Print on demand
Publication date: 04-2013
538 p. · 15.5x23.5 cm · Hardback
Description
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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.
Neural Network Architectures.- Learning paradigms.-
Reasoning and applications.- conclusions.
Reasoning and applications.- conclusions.
Reasoning and applications.- conclusions.
Contains the latest research in the area of neural information systems and their applications
Written by leading experts
State-of-the-Art of the book