Advances in Neural Information Processing Systems 12

Advances in Neural Information Processing Systems 12
Author: Sara A. Solla
Publisher: MIT Press
Total Pages: 1124
Release: 2000
Genre: Computers
ISBN: 9780262194501

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 10

Advances in Neural Information Processing Systems 10
Author: Michael I. Jordan
Publisher: MIT Press
Total Pages: 1114
Release: 1998
Genre: Computers
ISBN: 9780262100762

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

Advances in Neural Information Processing Systems 11
Author: Michael S. Kearns
Publisher: MIT Press
Total Pages: 1122
Release: 1999
Genre: Computers
ISBN: 9780262112451

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.

Theory of Neural Information Processing Systems

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

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.

Predicting Structured Data

Predicting Structured Data
Author: Neural Information Processing Systems Foundation
Publisher: MIT Press
Total Pages: 361
Release: 2007
Genre: Algorithms
ISBN: 0262026171

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

Advances in Neural Information Processing Systems

Advances in Neural Information Processing Systems
Author: Thomas G. Dietterich
Publisher: MIT Press
Total Pages: 832
Release: 2002-09
Genre: Computers
ISBN: 9780262042086

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.

Advances in Neural Information Processing Systems 16

Advances in Neural Information Processing Systems 16
Author: Sebastian Thrun
Publisher: MIT Press
Total Pages: 1694
Release: 2004
Genre: Models, Neurological
ISBN: 9780262201520

Papers presented at the 2003 Neural Information Processing Conference by leading physicists, neuroscientists, mathematicians, statisticians, and computer scientists. The annual Neural Information Processing (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 thirty percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. This volume contains all the papers presented at the 2003 conference.

Reinforcement Learning

Reinforcement Learning
Author: Marco Wiering
Publisher: Springer Science & Business Media
Total Pages: 653
Release: 2012-03-05
Genre: Technology & Engineering
ISBN: 3642276458

Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and adaptive behavior of intelligent agents. As a field, reinforcement learning has progressed tremendously in the past decade. The main goal of this book is to present an up-to-date series of survey articles on the main contemporary sub-fields of reinforcement learning. This includes surveys on partially observable environments, hierarchical task decompositions, relational knowledge representation and predictive state representations. Furthermore, topics such as transfer, evolutionary methods and continuous spaces in reinforcement learning are surveyed. In addition, several chapters review reinforcement learning methods in robotics, in games, and in computational neuroscience. In total seventeen different subfields are presented by mostly young experts in those areas, and together they truly represent a state-of-the-art of current reinforcement learning research. Marco Wiering works at the artificial intelligence department of the University of Groningen in the Netherlands. He has published extensively on various reinforcement learning topics. Martijn van Otterlo works in the cognitive artificial intelligence group at the Radboud University Nijmegen in The Netherlands. He has mainly focused on expressive knowledge representation in reinforcement learning settings.