Unsupervised Learning: Foundations of Neural Computation

Authors

  • DeLiang Wang

DOI:

https://doi.org/10.1609/aimag.v22i2.1565

Abstract

Unsupervised Learning: Foundations of Neural Computation is a collection of 21 papers published in the journal Neural Computation in the 10-year period since its founding in 1989 by Terrence Sejnowski. Neural Computation has become the leading journal of its kind. The editors of the book are Geoffrey Hinton and Terrence Sejnowski, two pioneers in neural networks. The selected papers include some of the most influential titles of late, for example, "What Is the Goal of Sensory Coding" by David Field and "An Information-Maximization Approach to Blind Separation and Blind Deconvolution" by Anthony Bell and Terrence Sejnowski. The edited volume provides a sample of important works on unsupervised learning, which cut across the fields of

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Published

2001-06-15

How to Cite

Wang, D. (2001). Unsupervised Learning: Foundations of Neural Computation. AI Magazine, 22(2), 101. https://doi.org/10.1609/aimag.v22i2.1565

Issue

Vol. 22 No. 2: Summer 2001

Section

Book Reviews

License

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