We present and derive a new stick-breaking construction of the beta process. The construction is closely related to a special case of the stick-breaking construction of the Dirich-let process (Sethuraman, 1994) applied to the beta distribution. We derive an inference procedure that relies on Monte Carlo integration to reduce the number of parameters to be inferred, and present results on synthetic data, the MNIST handwritten digits data set and a time-evolving gene expression data set. Copyright 2010 by the author(s)/owner(s).
|Original language||English (US)|
|Title of host publication||ICML 2010 - Proceedings, 27th International Conference on Machine Learning|
|Number of pages||8|
|State||Published - Sep 17 2010|