The Infinite Hierarchical Factor Regression Model

We propose a nonparametric Bayesian factor regression model that accounts for uncertainty in the number of factors, and the relationship between factors. To accomplish this, we propose a sparse variant of the Indian Buffet Process and couple this with a hierarchical model over factors, based on Kingman's coalescent. We apply this model to two problems (factor analysis and factor regression) in gene-expression data analysis.

• Type: Conference
• Year: 2008
• Where: NIPS
• Authors: Piyush Rai, Hal Daumé III
• Keywords: Factor Regression, Factor Regression Model, Indian Buffet Process, Information Technology, NIPS 2008