Handbook on Neural Information Processing

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Handbook on Neural Information Processing is written by Monica Bianchini and published by Springer Science & Business Media. It's available with International Standard Book Number or ISBN identification 3642366570 (ISBN 10) and 9783642366574 (ISBN 13).

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.