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An introduction to the Mondrian Process

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If you have a question about this talk, please contact Zoubin Ghahramani.

The Mondrian process is a probability distribution over guillotine partitions of Euclidean space introduced by Daniel Roy and Yee Whye Teh in 2009. It can be seen as a generalization of the Dirichlet process to higher dimensional spaces and possesses an elegant self-consistency property. In this talk I would like to introduce the Mondrian process, describe its properties and try to give some intuition for where these properties come from. Finally I will describe applications of Mondrians in online classification, where they form basis of an efficient online random forest algorithm, and in relational modelling, where they can be used as a nonparametric prior distribution.

This talk is part of the Machine Learning @ CUED series.

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