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Revision as of 20:52, 7 February 2009
Bibliographical Data
Title: | Gaussian Processes for Machine Learning |
Author: | Carl Edward Rasmussen, Christopher K. I. Williams |
Subjects: | Computer Science |
Key words: | gaussian processes, gaussian, machine learning, artifiical intelligence, markov process, regression, classification, support vector machines, splines, neural networks, relevance vector machines |
Education Level: | Higher Education |
License: | All Rights Reserved - Standard Copyright |
Description: | From the site:
Gaussian processes (GPs) provide a principled, practical, probabilistic approach to learning in kernel machines. GPs have received increased attention in the machine-learning community over the past decade, and this book provides a long-needed systematic and unified treatment of theoretical and practical aspects of GPs in machine learning. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics. |
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URL: | http://www.gaussianprocess.org/gpml/ |
Download link: | http://www.gaussianprocess.org/gpml/chapters |
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