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Handbook on Neural Information Processing

Bag om Handbook on Neural Information Processing

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.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783642366567
  • Indbinding:
  • Hardback
  • Sideantal:
  • 538
  • Udgivet:
  • 12. april 2013
  • Udgave:
  • 2013
  • Størrelse:
  • 242x171x35 mm.
  • Vægt:
  • 974 g.
  • BLACK WEEK
  Gratis fragt
Leveringstid: 8-11 hverdage
Forventet levering: 9. december 2024

Beskrivelse af Handbook on Neural Information Processing

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.

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