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 Title: Gaussian Processes for Machine Learning
 Author(s): Carl Edward Rasmussen, Christopher K. I. Williams
 Publisher: The MIT Press (November 23, 2005)
 Permission: "The MIT Press have kindly agreed to allow us to make the book available on the web."
 Hardcover/Paperback: 266 pages
 eBook: PDF Files
 Language: English
 ISBN10: 026218253X
 ISBN13: 9780262182539
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Book Description
Gaussian Processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machinelearning community over the past decade, and this book provides a longneeded systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and selfcontained, targeted at researchers and students in machine learning and applied statistics.
The book deals with the supervisedlearning problem for both regression and classification, and includes detailed algorithms. A wide variety of covariance (kernel) functions are presented and their properties discussed.
Model selection is discussed both from a Bayesian and a classical perspective. Many connections to other wellknown techniques from machine learning and statistics are discussed, including supportvector machines, neural networks, splines, regularization networks, relevance vector machines and others.
Theoretical issues including learning curves and the PACBayesian framework are treated, and several approximation methods for learning with large datasets are discussed.
The book contains illustrative examples and exercises, and code and datasets are available on the Web. Appendixes provide mathematical background and a discussion of Gaussian Markov processes.
About the Authors Carl Edward Rasmussen is a Lecturer at the Department of Engineering, University of Cambridge, and Adjunct Research Scientist at the Max Planck Institute for Biological Cybernetics, TÃ¼bingen.
 Machine Learning
 Probability and Stochastic Processes
 Statistics and SAS Programming
 Artificial Intelligence
 Data Analysis and Data Mining
 Neural Networks
 Gaussian Processes for Machine Learning (Carl Edward Rasmussen, et al.)
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