Neural Information Processing

Author : Michael C. Mozer,Michael I. Jordan,Thomas Petsche
Publisher : MIT Press
Page : 1128 pages
File Size : 51,6 Mb
Release : 1997
Category : Artificial intelligence
ISBN : 0262100657

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Advances in Neural Information Processing Systems 9 by Michael C. Mozer,Michael I. Jordan,Thomas Petsche Pdf

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 neural networks and genetic algorithms, cognitive science, neuroscience and biology, computer science, AI, applied mathematics, physics, and many branches of engineering. Only about 30% of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. All of the papers presented appear in these proceedings.

Author : Lawrence K. Saul,Yair Weiss,Léon Bottou
Publisher : MIT Press
Page : 1710 pages
File Size : 49,7 Mb
Release : 2005
Category : Computational intelligence
ISBN : 0262195348

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Advances in Neural Information Processing Systems 17 by Lawrence K. Saul,Yair Weiss,Léon Bottou Pdf

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.

Author : Suzanna Becker,Sebastian Thrun,Klaus Obermayer
Publisher : MIT Press
Page : 1738 pages
File Size : 45,7 Mb
Release : 2003
Category : Neural circuitry
ISBN : 0262025507

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Advances in Neural Information Processing Systems 15 by Suzanna Becker,Sebastian Thrun,Klaus Obermayer Pdf

Proceedings of the 2002 Neural Information Processing Systems Conference.

Author : P Bartlett,F. C.N Pereira,C. J. C. Burges,L Bottou,K. Q Weinberger
Publisher : Unknown
Page : 3328 pages
File Size : 48,9 Mb
Release : 2013
Category : Neural computers
ISBN : 162748003X

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Advances in Neural Information Processing Systems 25 by P Bartlett,F. C.N Pereira,C. J. C. Burges,L Bottou,K. Q Weinberger Pdf

Author : Michael I. Jordan,Michael J. Kearns,Sara A. Solla
Publisher : MIT Press
Page : 1114 pages
File Size : 49,9 Mb
Release : 1998
Category : Computers
ISBN : 0262100762

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Advances in Neural Information Processing Systems 10 by Michael I. Jordan,Michael J. Kearns,Sara A. Solla Pdf

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.

Author : Sara A. Solla,Klaus-Robert Müller,Todd K. Leen
Publisher : MIT Press
Page : 1124 pages
File Size : 46,9 Mb
Release : 2000
Category : Computers
ISBN : 0262194503

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Advances in Neural Information Processing Systems 12 by Sara A. Solla,Klaus-Robert Müller,Todd K. Leen Pdf

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.

Author : Michael S. Kearns,Sara A. Solla,David A. Cohn
Publisher : MIT Press
Page : 1122 pages
File Size : 49,8 Mb
Release : 1999
Category : Computers
ISBN : 0262112450

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Advances in Neural Information Processing Systems 11 by Michael S. Kearns,Sara A. Solla,David A. Cohn Pdf

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.

Author : A.C.C. Coolen,R. Kuehn,P. Sollich
Publisher : OUP Oxford
Page : 596 pages
File Size : 52,9 Mb
Release : 2005-07-21
Category : Neural networks (Computer science)
ISBN : 0191583006

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Theory of Neural Information Processing Systems by A.C.C. Coolen,R. Kuehn,P. Sollich Pdf

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.

Author : Todd K. Leen,Thomas G. Dietterich,Volker Tresp
Publisher : MIT Press
Page : 1136 pages
File Size : 54,9 Mb
Release : 2001
Category : Artificial intelligence
ISBN : 0262122413

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Advances in Neural Information Processing Systems 13 by Todd K. Leen,Thomas G. Dietterich,Volker Tresp Pdf

The proceedings of the 2000 Neural Information Processing Systems (NIPS) Conference.The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. The conference is interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, vision, speech and signal processing, reinforcement learning and control, implementations, and diverse applications. 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 at the 2000 conference.

Author : Thomas G. Dietterich,Suzanna Becker,Professor of Information Engineering Zoubin Ghahramani,Zoubin Ghahramani
Publisher : MIT Press
Page : 856 pages
File Size : 40,6 Mb
Release : 2002-09
Category : Computers
ISBN : 0262042088

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Advances in Neural Information Processing Systems by Thomas G. Dietterich,Suzanna Becker,Professor of Information Engineering Zoubin Ghahramani,Zoubin Ghahramani Pdf

The proceedings of the 2001 Neural Information Processing Systems (NIPS) Conference. The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. The conference is interdisciplinary, with contributions in algorithms, learning theory, cognitive science, neuroscience, vision, speech and signal processing, reinforcement learning and control, implementations, and diverse applications. 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 at the 2001 conference.

Author : Terrence J. Sejnowski
Publisher : MIT Press
Page : 354 pages
File Size : 50,7 Mb
Release : 2018-10-23
Category : Computers
ISBN : 9780262038034

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The Deep Learning Revolution by Terrence J. Sejnowski Pdf

How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

Author : Gerald Tesauro,David S. Touretzky,Todd Leen
Publisher : MIT Press
Page : 1180 pages
File Size : 45,9 Mb
Release : 1995
Category : Computers
ISBN : 0262201046

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Advances in Neural Information Processing Systems 7 by Gerald Tesauro,David S. Touretzky,Todd Leen Pdf

November 28-December 1, 1994, Denver, Colorado NIPS is the longest running annual meeting devoted to Neural Information Processing Systems. Drawing on such disparate domains as neuroscience, cognitive science, computer science, statistics, mathematics, engineering, and theoretical physics, the papers collected in the proceedings of NIPS7 reflect the enduring scientific and practical merit of a broad-based, inclusive approach to neural information processing. The primary focus remains the study of a wide variety of learning algorithms and architectures, for both supervised and unsupervised learning. The 139 contributions are divided into eight parts: Cognitive Science, Neuroscience, Learning Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Visual Processing, and Applications. Topics of special interest include the analysis of recurrent nets, connections to HMMs and the EM procedure, and reinforcement- learning algorithms and the relation to dynamic programming. On the theoretical front, progress is reported in the theory of generalization, regularization, combining multiple models, and active learning. Neuroscientific studies range from the large-scale systems such as visual cortex to single-cell electrotonic structure, and work in cognitive scientific is closely tied to underlying neural constraints. There are also many novel applications such as tokamak plasma control, Glove-Talk, and hand tracking, and a variety of hardware implementations, with particular focus on analog VLSI.

Author : Neural Information Processing Systems Foundation
Publisher : MIT Press
Page : 361 pages
File Size : 50,9 Mb
Release : 2007
Category : Algorithms
ISBN : 9780262026178

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Predicting Structured Data by Neural Information Processing Systems Foundation Pdf

State-of-the-art algorithms and theory in a novel domain of machine learning, prediction when the output has structure.

Author : Guido Dornhege,Jose del R. Millan,Thilo Hinterberger,Dennis J. McFarland,Klaus-Robert Müller
Publisher : MIT Press
Page : 520 pages
File Size : 40,5 Mb
Release : 2007
Category : Brain mapping
ISBN : 9780262042444

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Toward Brain-computer Interfacing by Guido Dornhege,Jose del R. Millan,Thilo Hinterberger,Dennis J. McFarland,Klaus-Robert Müller Pdf

This volume presents a timely overview of the latest BCI research, with contributions from many of the important research groups in the field.

Author : Bing J. Sheu,Joongho Choi
Publisher : Springer Science & Business Media
Page : 569 pages
File Size : 42,7 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461522478

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Neural Information Processing and VLSI by Bing J. Sheu,Joongho Choi Pdf

Neural Information Processing and VLSI provides a unified treatment of this important subject for use in classrooms, industry, and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analog and digital VLSI parallel processing techniques. Neural Information Processing and VLSI systematically presents various neural network paradigms, computing architectures, and the associated electronic/optical implementations using efficient VLSI design methodologies. Conventional digital machines cannot perform computationally-intensive tasks with satisfactory performance in such areas as intelligent perception, including visual and auditory signal processing, recognition, understanding, and logical reasoning (where the human being and even a small living animal can do a superb job). Recent research advances in artificial and biological neural networks have established an important foundation for high-performance information processing with more efficient use of computing resources. The secret lies in the design optimization at various levels of computing and communication of intelligent machines. Each neural network system consists of massively paralleled and distributed signal processors with every processor performing very simple operations, thus consuming little power. Large computational capabilities of these systems in the range of some hundred giga to several tera operations per second are derived from collectively parallel processing and efficient data routing, through well-structured interconnection networks. Deep-submicron very large-scale integration (VLSI) technologies can integrate tens of millions of transistors in a single silicon chip for complex signal processing and information manipulation. The book is suitable for those interested in efficient neurocomputing as well as those curious about neural network system applications. It has been especially prepared for use as a text for advanced undergraduate and first year graduate students, and is an excellent reference book for researchers and scientists working in the fields covered.