title: Tree-Structured Infinite Sparse Factor Model.
abstract: 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.
authors.affiliation: Electrical & Computer Engineering Department, Duke University, Durham, NC, USA.
authors.forename: XianXing
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Statistical Sciences, Duke University, Durham, NC, USA.
authors.forename: David B
authors.initials: DB
authors.lastname: Dunson
authors.affiliation: Electrical & Computer Engineering Department, Duke University, Durham, NC, USA.
authors.forename: Lawrence
authors.initials: L
authors.lastname: Carin