nips nips2008 nips2008-235 nips2008-235-reference knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Piyush Rai, Hal Daume
Abstract: 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. 1
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