Gaussian Processes for Machine Learning
A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.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. The book dea…
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Produktdetails
Weitere Autoren: Williams, Christopher K. I.
- ISBN: 978-0-262-18253-9
- EAN: 9780262182539
- Produktnummer: 1914422
- Verlag: MIT Press
- Sprache: Englisch
- Erscheinungsjahr: 2005
- Seitenangabe: 272 S.
- Masse: H26.2 cm x B21.0 cm x D1.8 cm 764 g
- Gewicht: 764
- Sonstiges: Professional & Vocational
Über den Autor
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, Tübingen.Christopher K. I. Williams is Professor of Machine Learning and Director of the Institute for Adaptive and Neural Computation in the School of Informatics, University of Edinburgh.
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