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Neural Network Design and the Complexity of Learning by J. Stephen Judd is a nonfiction available to read on EtoBox.

What is Neural Network Design and the Complexity of Learning about?

Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the computational difficulties in training neural networks and explores how certain design principles will or will not make the problems easier. Judd looks beyond the scope of any one particular learning rule, at a level above the details of neurons. There he finds new issues that arise when great numbers of neurons are employed and he offers fresh insights into design principles that could guide the construction of artificial and biological neural networks. The first part of the book describes the motivations and goals of the study and relates them to current scientific theory. It provides an overview of the major ideas, formulates the general learning problem with an eye to the computational complexity of the task, reviews current theory on learning, relates the book's model of learning to other models outside the connectionist paradigm, and sets out to examine scale-up issues in connectionist learning. Later chapters prove the intractability of the general case of memorizing in networks, elaborate on implications of this intrac

Who reads Neural Network Design and the Complexity of Learning?

Author

J. Stephen Judd

Publisher

The MIT Press

Published

1990

Language

EN

ISBN

9780262276559

Category

nonfiction

Subjects

Psychology, Computer Science, Social_sciences