A tree-structured multiplicative gamma process (TMGP) is developed, for inferring the depth of a tree-based factor-analysis model. This new model is coupled with the nested Chinese restaurant process, to nonparametrically infer the depth and width (structure) of the tree. In addition to developing the model, theoretical properties of the TMGP are addressed, and a novel MCMC sampler is developed. The structure of the inferred tree is used to learn relationships between high-dimensional data, and the model is also applied to compressive sensing and interpolation of incomplete images. Copyright 2011 by the author(s)/owner(s).
|Original language||English (US)|
|Title of host publication||Proceedings of the 28th International Conference on Machine Learning, ICML 2011|
|Number of pages||8|
|State||Published - Oct 7 2011|