Handbook on Neural Information Processing

✍ Scribed by Yoshua Bengio, Aaron Courville (auth.), Monica Bianchini, Marco Maggini, Lakhmi C. Jain (eds.)

• Publisher: Springer-Verlag Berlin Heidelberg
• Year: 2013
• Tongue: English
• Leaves: 546
• Series: Intelligent Systems Reference Library 49
• Edition: 1
• Category: Library

✦ Synopsis

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.

✦ Table of Contents

Front Matter....Pages 1-18
Deep Learning of Representations....Pages 1-28
Recurrent Neural Networks....Pages 29-65
Supervised Neural Network Models for Processing Graphs....Pages 67-96
Topics on Cellular Neural Networks....Pages 97-141
Approximating Multivariable Functions by Feedforward Neural Nets....Pages 143-181
Bochner Integrals and Neural Networks....Pages 183-214
Semi-supervised Learning....Pages 215-239
Statistical Relational Learning....Pages 241-281
Kernel Methods for Structured Data....Pages 283-333
Multiple Classifier Systems: Theory, Applications and Tools....Pages 335-378
Self Organisation and Modal Learning: Algorithms and Applications....Pages 379-400
Bayesian Networks, Introduction and Practical Applications....Pages 401-431
Relevance Feedback in Content-Based Image Retrieval: A Survey....Pages 433-469
Learning Structural Representations of Text Documents in Large Document Collections....Pages 471-503
Neural Networks in Bioinformatics....Pages 505-525
Back Matter....Pages 527-537

✦ Subjects

Computational Intelligence; Artificial Intelligence (incl. Robotics)