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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...

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Bibliographic Details
Call Number:Libro Electrónico
Main Author: Rasmussen, Carl Edward
Other Authors: Williams, Christopher K. I.
Format: Electronic eBook
Language:Inglés
Published: Cambridge, Mass. : MIT Press, ©2006.
Series:Adaptive computation and machine learning.
Subjects:
Online Access:Texto completo
Table of Contents:
  • Regression
  • Classification
  • Covariance functions
  • Model selection and adaptation of hyperparameters
  • Relationships between GPs and other models
  • Theoretical perspectives
  • Approximation methods for large datasets
  • Appendix A : Mathematical background
  • Appendix B : Guassian Markov processes.