An Introduction To Neural Information Processing

Author : Todd K. Leen,Thomas G. Dietterich,Volker Tresp
Publisher : MIT Press
Page : 1136 pages
File Size : 47,9 Mb
Release : 2001
Category : Artificial intelligence
ISBN : 0262122413

Get Book

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 : 832 pages
File Size : 42,5 Mb
Release : 2002-09
Category : Computers
ISBN : 0262042088

Get Book

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 : Michael S. Kearns,Sara A. Solla,David A. Cohn
Publisher : MIT Press
Page : 1122 pages
File Size : 46,7 Mb
Release : 1999
Category : Computers
ISBN : 0262112450

Get Book

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 : 49,7 Mb
Release : 2005-07-21
Category : Neural networks (Computer science)
ISBN : 0191583006

Get Book

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 : Lawrence K. Saul,Yair Weiss,Léon Bottou
Publisher : MIT Press
Page : 1710 pages
File Size : 48,9 Mb
Release : 2005
Category : Computational intelligence
ISBN : 0262195348

Get Book

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 : Peiji Liang,Si Wu,Fanji Gu
Publisher : Springer
Page : 328 pages
File Size : 52,9 Mb
Release : 2015-12-22
Category : Medical
ISBN : 9789401773935

Get Book

An Introduction to Neural Information Processing by Peiji Liang,Si Wu,Fanji Gu Pdf

This book provides an overview of neural information processing research, which is one of the most important branches of neuroscience today. Neural information processing is an interdisciplinary subject, and the merging interaction between neuroscience and mathematics, physics, as well as information science plays a key role in the development of this field. This book begins with the anatomy of the central nervous system, followed by an introduction to various information processing models at different levels. The authors all have extensive experience in mathematics, physics and biomedical engineering, and have worked in this multidisciplinary area for a number of years. They present classical examples of how the pioneers in this field used theoretical analysis, mathematical modeling and computer simulation to solve neurobiological problems, and share their experiences and lessons learned. The book is intended for researchers and students with a mathematics, physics or informatics background who are interested in brain research and keen to understand the necessary neurobiology and how they can use their specialties to address neurobiological problems. It is also provides inspiration for neuroscience students who are interested in learning how to use mathematics, physics or informatics approaches to solve problems in their field.

Author : Bing J. Sheu,Joongho Choi
Publisher : Springer Science & Business Media
Page : 569 pages
File Size : 52,6 Mb
Release : 2012-12-06
Category : Technology & Engineering
ISBN : 9781461522478

Get Book

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.

Author : David S. Touretzky,Michael C. Mozer,Michael E. Hasselmo
Publisher : MIT Press
Page : 1128 pages
File Size : 40,6 Mb
Release : 1996
Category : Computers
ISBN : 0262201070

Get Book

Advances in Neural Information Processing Systems 8 by David S. Touretzky,Michael C. Mozer,Michael E. Hasselmo Pdf

The past decade has seen greatly increased interaction between theoretical work in neuroscience, cognitive science and information processing, and experimental work requiring sophisticated computational modeling. The 152 contributions in NIPS 8 focus on a wide variety of algorithms and architectures for both supervised and unsupervised learning. They are divided into nine parts: Cognitive Science, Neuroscience, Theory, Algorithms and Architectures, Implementations, Speech and Signal Processing, Vision, Applications, and Control. Chapters describe how neuroscientists and cognitive scientists use computational models of neural systems to test hypotheses and generate predictions to guide their work. This work includes models of how networks in the owl brainstem could be trained for complex localization function, how cellular activity may underlie rat navigation, how cholinergic modulation may regulate cortical reorganization, and how damage to parietal cortex may result in neglect. Additional work concerns development of theoretical techniques important for understanding the dynamics of neural systems, including formation of cortical maps, analysis of recurrent networks, and analysis of self- supervised learning. Chapters also describe how engineers and computer scientists have approached problems of pattern recognition or speech recognition using computational architectures inspired by the interaction of populations of neurons within the brain. Examples are new neural network models that have been applied to classical problems, including handwritten character recognition and object recognition, and exciting new work that focuses on building electronic hardware modeled after neural systems. A Bradford Book

Author : Michael I. Jordan,Michael J. Kearns,Sara A. Solla
Publisher : MIT Press
Page : 1114 pages
File Size : 41,5 Mb
Release : 1998
Category : Computers
ISBN : 0262100762

Get Book

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 : Suzanna Becker,Sebastian Thrun,Klaus Obermayer
Publisher : MIT Press
Page : 1738 pages
File Size : 42,9 Mb
Release : 2003
Category : Neural circuitry
ISBN : 0262025507

Get Book

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 : Marcel van Gerven,Sander Bohte
Publisher : Frontiers Media SA
Page : 220 pages
File Size : 40,8 Mb
Release : 2018-02-01
Category : Electronic
ISBN : 9782889454013

Get Book

Artificial Neural Networks as Models of Neural Information Processing by Marcel van Gerven,Sander Bohte Pdf

Modern neural networks gave rise to major breakthroughs in several research areas. In neuroscience, we are witnessing a reappraisal of neural network theory and its relevance for understanding information processing in biological systems. The research presented in this book provides various perspectives on the use of artificial neural networks as models of neural information processing. We consider the biological plausibility of neural networks, performance improvements, spiking neural networks and the use of neural networks for understanding brain function.

Author : Kevin Gurney
Publisher : CRC Press
Page : 234 pages
File Size : 47,6 Mb
Release : 2018-10-08
Category : Computers
ISBN : 9781482286991

Get Book

An Introduction to Neural Networks by Kevin Gurney Pdf

Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.

Author : Neural Information Processing Systems
Publisher : Curran Associates Incorporated
Page : 2348 pages
File Size : 48,5 Mb
Release : 2010
Category : Computers
ISBN : 1615679111

Get Book

Advances in Neural Information Processing Systems 22 by Neural Information Processing Systems Pdf

Author : Guy Van den Broeck,Kristian Kersting,Sriraam Natarajan,David Poole
Publisher : MIT Press
Page : 455 pages
File Size : 40,7 Mb
Release : 2021-08-17
Category : Computers
ISBN : 9780262542593

Get Book

An Introduction to Lifted Probabilistic Inference by Guy Van den Broeck,Kristian Kersting,Sriraam Natarajan,David Poole Pdf

Recent advances in the area of lifted inference, which exploits the structure inherent in relational probabilistic models. Statistical relational AI (StaRAI) studies the integration of reasoning under uncertainty with reasoning about individuals and relations. The representations used are often called relational probabilistic models. Lifted inference is about how to exploit the structure inherent in relational probabilistic models, either in the way they are expressed or by extracting structure from observations. This book covers recent significant advances in the area of lifted inference, providing a unifying introduction to this very active field. After providing necessary background on probabilistic graphical models, relational probabilistic models, and learning inside these models, the book turns to lifted inference, first covering exact inference and then approximate inference. In addition, the book considers the theory of liftability and acting in relational domains, which allows the connection of learning and reasoning in relational domains.

Author : Anthony C. C. Coolen,Reimer Kühn,Peter Sollich
Publisher : Oxford University Press, USA
Page : 569 pages
File Size : 45,8 Mb
Release : 2005
Category : Computers
ISBN : 0198530234

Get Book

Theory of Neural Information Processing Systems by Anthony C. C. Coolen,Reimer Kühn,Peter Sollich Pdf

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.