Computer Science – Learning
Scientific paper
2009-08-05
NIPS 2008
Computer Science
Learning
Scientific paper
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.
III Hal Daume
Rai Piyush
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