PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

The Mondrian Process
Yee Whye Teh and Daniel Roy
In: NIPS 2008, 08 Dec - 13 Dec 2008, Vancouver, Canada.


We describe a novel class of distributions, called Mondrian processes, which can be interpreted as probability distributions over kd-tree data structures. Mondrian processes are multidimensional generalizations of Poisson processes and this connection allows us to construct multidimensional generalizations of the stick-breaking process described by Sethuraman (1994), recovering the Dirichlet process in one dimension. After introducing the Aldous-Hoover representation for jointly and separately exchangeable arrays, we show how the process can be used as a nonparametric prior distribution in Bayesian models of relational data.

PDF - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Theory & Algorithms
ID Code:4694
Deposited By:Yee Whye Teh
Deposited On:24 March 2009