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Gaussian processes for machine learning

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"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."--Jacket.OCLC-licensed vendor bibliographic record.

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Detail Information

Series Title

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Call Number

510 RAS g

Publisher

Cambridge, Mass. : : MIT Press,., 2006.

Collation

1 online resource (xviii, 248 pages) : illustrations.

Language

English

ISBN/ISSN

9780262256834

Classification

510

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

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Subject(s)

Machine Learning
Gaussian processes

Specific Detail Info

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Statement of Responsibility

Carl Edward Rasmussen, Christopher K.I. Williams.

Other Information

Cataloger

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Source

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Validator

maya

Digital Object Identifier (DOI)

https://doi.org/10.7551/mitpress/3206.001.0001

Journal Volume

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Journal Issue

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Subtitle

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Parallel Title

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