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titleBayesian inference: An introduction to principles and practice in machine learning
authorsMichael E. Tipping
keywords
abstractThis article gives a basic introduction to the principles of Bayesian inference in a machine learning context, with an emphasis on the importance of marginalisation for dealing with uncertainty. We begin by illustrating concepts via a simple regression task before relating ideas to practical, contemporary, techniques with a description of `sparse Bayesian' models and the `relevance vector machine'.
typeChapter
journalAdvanced Lectures on Machine Learning
published year
serial1262
is_viewableyes
(Total records:1429)
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