Unsupervised Learning

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Since its founding in 1989 by Terrence Sejnowski, Neural Computation hasbecome the leading journal in the field. Foundations of Neural Computationcollects, by topic, the most significant papers that have appeared in the journal over thepast nine years.This volume of Foundations of Neural Computation, on unsupervisedlearning algorithms, focuses on neural network learning algorithms that do notrequire an explicit teacher. The goal of unsupervised learning is to extract anefficient internal representation of the statistical structure implicit in theinputs. These algorithms provide insights into the development of the cerebralcortex and implicit learning in humans. They are also of interest to engineersworking in areas such as computer vision and speech recognition who seek efficientrepresentations of raw input data.