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
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.
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.
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.
Inhaltsverzeichnis
Neural Network Architectures.- Learning paradigms.- Reasoning and applications.- conclusions. Reasoning and applications.- conclusions. Reasoning and applications.- conclusions.
Klappentext
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 rnRecurrent, recursive, and graph neural networks rnCellular neural networks rnBayesian networks rnApproximation capabilities of neural networks rnSemi-supervised learning rnStatistical relational learning rn Kernel methods for structured data rn Multiple classifier systems rn Self organisation and modal learning rn Applications to content-based image retrieval, text mining in large document collections, and bioinformatics rnrnrn rnThis book is thought particularly for graduate students, researchers and practitioners, willing to deepen their knowledge on more advanced connectionist models and related learning paradigms.
Contains the latest research in the area of neural information systems and their applications
rn
Written by leading experts
rn
State-of-the-Art of the book
rn
