Handbook On Neural Information Processing (intelligent Systems Reference Library)
by Lakhmi C. Jain /
2013 / English / PDF
8.3 MB Download
This handbook presents some of the most recent topics in neural
information processing, covering both theoretical concepts and
practical applications. The contributions include:
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
Deep architecturesRecurrent, recursive, and graph neural networks
Recurrent, recursive, and graph neural networksCellular neural networks
Cellular neural networksBayesian networks
Bayesian networksApproximation capabilities of neural networks
Approximation capabilities of neural networksSemi-supervised learning
Semi-supervised learningStatistical relational learning
Statistical relational learning Kernel methods for structured data
Kernel methods for structured data Multiple classifier systems
Multiple classifier systems Self organisation and modal learning
Self organisation and modal learning Applications to content-based image retrieval, text
mining in large document collections, and bioinformatics
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.
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.
