Mit press series on adaptive computation and machine learning seeks to unify the many diverse strands of machine learning research and to foster high quality research and innovative applications one of the most active directions in machine learning has been the de velopment of practical bayesian methods for challenging learning problems. Gaussian processes for machine learning adaptive computation and machine learning series carl edward rasmussen christopher k i williams on amazoncom free shipping on qualifying offers a comprehensive and self contained introduction to gaussian processes which provide a principled practical. Gaussian processes for machine learning chris williams institute for adaptive and neural computation school of informatics university of edinburgh uk august 2007 chris williams anc gaussian processes for machine learning. Gaussian processes for machine learning matthias seeger department of eecs university of california at berkeley 485 soda hall berkeley ca 94720 1776 usa mseegercsberkeleyedu february 24 2004 abstract gaussian processes gps are natural generalisations of multivariate gaussian ran dom variables to in nite countably or continuous index sets. 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
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