Innovations in Neural Information Paradigms and Applications - Studies in Computational Intelligence.

This research book presents some of the most recent advances in neural information processing models including both theoretical concepts and practical applications. The contributions include: Advances in neural information processing paradigms; Self organising structures; Unsupervised and supervised learning of graph domains; Neural grammar networks; Model complexity in neural network learning; Regularization and suboptimal solutions in neural learning; Neural networks for the classification of vectors, sequences and graphs; Metric learning for prototype-based classification; Ensembles of neural networks; Fraud detection using machine learning; Computational modelling of neural multimodal integration. This book is directed to the researchers, graduate students, professors and practitioner interested in recent advances in neural information processing paradigms and applications.