Handbook on Neural Information Processing Cover

Handbook on Neural Information Processing

ISBN/ASIN: 9783642366567,9783642366574 | 2013 | English | pdf | 538/546 pages | 8.26 Mb
Publisher: Springer-Verlag Berlin Heidelberg | Author: Yoshua Bengio, Aaron Courville (auth.), Monica Bianchini, Marco Maggini, Lakhmi C. Jain (eds.) | Edition: 1

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

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