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Gaussian processes for machine learning /
"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 an...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Otros Autores: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Cambridge, Mass. :
MIT Press,
©2006.
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| Colección: | Adaptive computation and machine learning.
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| Temas: | |
| Acceso en línea: | Texto completo |
| Sumario: | "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 |
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| Descripción Física: | 1 online resource (xviii, 248 pages) : illustrations |
| Bibliografía: | Includes bibliographical references (pages 223-238) and indexes. |
| ISBN: | 9780262256834 0262256835 1423769902 9781423769903 9780262182539 026218253X 9786612097966 6612097965 1282097962 9781282097964 9786612096709 6612096705 0262261073 9780262261074 |
| Acceso: | Limited Users and Download Restrictions may Apply, ProQuest 1 User Licence. Available using University of Exeter Username and Password. |