Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning)
Publisher: The MIT Press | Author(s): Christopher K. I. Williams | ISBN:026218253X | Release Date: 01 December 2005 | 2.63 MB | Pages: 266 | deposifiles
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.