Roy, DM and Teh, YW (2009) The Mondrian process. Advances in Neural Information Processing Systems 21 - Proceedings of the 2008 Conference. pp. 1377-1384.Full text not available from this repository.
We describe a novel class of distributions, called Mondrian processes, which can be interpreted as probability distributions over κd-tree data structures. Mondrian processes are multidimensional generalizations of Poisson processes and this connection allows us to construct multidimensional generalizations of the stickbreaking 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.
|Divisions:||Div F > Computational and Biological Learning|
|Depositing User:||Cron Job|
|Date Deposited:||07 Mar 2014 12:14|
|Last Modified:||08 Dec 2014 02:13|