Theory of Neural Information Processing Systems

by A.C.C. Coolen
Theory of Neural Information Processing Systems
Author: A.C.C. Coolen
Publisher: OUP Oxford
Total Pages: 596
Release: 2005-07-21
Genre: Neural networks (Computer science)
ISBN: 9780191583001
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Theory of Neural Information Processing Systems provides an explicit, coherent, and up-to-date account of the modern theory of neural information processing systems. It has been carefully developed for graduate students from any quantitative discipline, including mathematics, computer science, physics, engineering or biology, and has been thoroughly class-tested by the authors over a period of some 8 years. Exercises are presented throughout the text and notes on historical background and further reading guide the student into the literature. All mathematical details are included and appendices provide further background material, including probability theory, linear algebra and stochastic processes, making this textbook accessible to a wide audience.

Theory of Neural Information Processing Systems

by Anthony C. C. Coolen
Theory of Neural Information Processing Systems
Author: Anthony C. C. Coolen
Publisher: Oxford University Press, USA
Total Pages: 569
Release: 2005
Genre: Computers
ISBN: 9780198530237
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This interdisciplinary graduate text gives a full, explicit, coherent and up-to-date account of the modern theory of neural information processing systems and is aimed at student with an undergraduate degree in any quantitative discipline (e.g. computer science, physics, engineering, biology, or mathematics). The book covers all the major theoretical developments from the 1940s tot he present day, using a uniform and rigorous style of presentation and of mathematical notation. The text starts with simple model neurons and moves gradually to the latest advances in neural processing. An ideal textbook for postgraduate courses in artificial neural networks, the material has been class-tested. It is fully self contained and includes introductions to the various discipline-specific mathematical tools as well as multiple exercises on each topic.

Advances in Neural Information Processing Systems 10

by Michael I. Jordan
Advances in Neural Information Processing Systems 10
Author: Michael I. Jordan
Publisher: MIT Press
Total Pages: 1114
Release: 1998
Genre: Computers
ISBN: 9780262100762
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The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.

Advances in Neural Information Processing Systems 11

by Michael S. Kearns
Advances in Neural Information Processing Systems 11
Author: Michael S. Kearns
Publisher: MIT Press
Total Pages: 1122
Release: 1999
Genre: Computers
ISBN: 9780262112451
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The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.

Advances in Neural Information Processing Systems 17

by Lawrence K. Saul
Advances in Neural Information Processing Systems 17
Author: Lawrence K. Saul
Publisher: MIT Press
Total Pages: 1710
Release: 2005
Genre: Computational intelligence
ISBN: 9780262195348
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Papers presented at NIPS, the flagship meeting on neural computation, held in December 2004 in Vancouver.The annual Neural Information Processing Systems (NIPS) conference is the flagship meeting on neural computation. It draws a diverse group of attendees--physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The presentations are interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, brain imaging, vision, speech and signal processing, reinforcement learning and control, emerging technologies, and applications. Only twenty-five percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains the papers presented at the December, 2004 conference, held in Vancouver.

Advances in Neural Information Processing Systems 12

by Sara A. Solla
Advances in Neural Information Processing Systems 12
Author: Sara A. Solla
Publisher: MIT Press
Total Pages: 1124
Release: 2000
Genre: Computers
ISBN: 9780262194501
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The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.

Predicting Structured Data

by Neural Information Processing Systems Foundation
Predicting Structured Data
Author: Neural Information Processing Systems Foundation
Publisher: MIT Press
Total Pages: 361
Release: 2007
Genre: Algorithms
ISBN: 0262026171
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State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

Introduction To The Theory Of Neural Computation

by John A. Hertz
Introduction To The Theory Of Neural Computation
Author: John A. Hertz
Publisher: CRC Press
Total Pages: 352
Release: 2018-03-08
Genre: Science
ISBN: 0429968213
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Comprehensive introduction to the neural network models currently under intensive study for computational applications. It also provides coverage of neural network applications in a variety of problems of both theoretical and practical interest.