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ISBN: 9780262100458

ID: 17056174

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. 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 intractability and point out several corollaries applying to various special subcases. Judd refines the distinctive characteristics of the difficulties with families of shallow networks, addresses concerns about the ability of neural networks to generalize, and summarizes the results, implications, and possible extensions of the work. Neural Network Design and the Complexity of Learning is included in the Network Modeling and Connectionism series edited by Jeffrey Elman. Books, Computing~~Computer Science~~Artificial Intelligence, Neural Network Design And The Complexity Of Learning~~Book~~9780262100458~~J.Stephen Judd, , , , , , , , , ,, [PU: MIT Press]

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ISBN: 0262100452

ID: 4463032

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 intractability and point out several corollaries applying to various special subcases. Judd refines the distinctive characteristics of the difficulties with families of shallow networks, addresses concerns about the ability of neural networks to generalize, and summa artificial intelligence,behavioral sciences,certification,cognitive psychology,computer science,computers,computers and technology,health fitness and dieting,mathematics,networking Computer Science, The MIT Press

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ISBN: 0262100452

ID: 4463032

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 intractability and point out several corollaries applying to various special subcases. Judd refines the distinctive characteristics of the difficulties with families of shallow networks, addresses concerns about the ability of neural networks to generalize, and summa artificial intelligence,behavioral sciences,certification,cognitive psychology,computer science,computers and technology,health fitness and dieting,mathematics,networking,networks Psychology, The MIT Press

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ISBN: 9780262100458

ID: 5ab6ba2ebbca47552b157c26c28496b2

Neurocomputing is a one-volume encyclopedic source of information on neural networks, an essential guide to the background of concepts taken from disciplines as varied as neuroscience, psychology, cognitive science, engineering, and physics., [PU: MIT Press]

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ISBN: 9780262100458

ID: 9780262100458

Neural Network Design and the Complexity of Learning Author :J. Stephen Judd 9780262100458 0262100452, [PU: MIT Press]

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** Details of the book - Neural Network Design and the Complexity of Learning**

EAN (ISBN-13): 9780262100458

ISBN (ISBN-10): 0262100452

Hardcover

Publishing year: 1990

Publisher: MIT PR

172 Pages

Weight: 0,426 kg

Language: eng/Englisch

Book in our database since 31.10.2007 11:43:09

Book found last time on 15.04.2017 11:04:15

ISBN/EAN: 9780262100458

ISBN - alternate spelling:

0-262-10045-2, 978-0-262-10045-8

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