Gaussian processes for machine learning - Rasmussen Carl Edward (MIT Press, 2006)
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.
Keywords: Processus gaussiens Informatique; Apprentissage automatique Modèles mathématiques