Handbook on Neural Information Processing (Hardcover) (ISBN-13: 9783642366567)

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.

Author: Monica Bianchini
ISBN-10: 3642366562
ISBN-13: 9783642366567
Publisher: Springer
Language: English
Published: 04/26/2013
Pages: 538
Format: Hardcover
Weight: 2.10lbs
Size: 9.21h x 6.14w x 1.19d