Browsing Duke Dissertations by Subject "machine learning"

Now showing items 1-2 of 2

Machine Learning with Dirichlet and Beta Process Priors: Theory and Applications

Paisley, John William (2010)

<p>Bayesian nonparametric methods are useful for modeling data without having to define the complexity of the entire model <italic>a priori</italic>, but rather allowing for this complexity to be determined by the data. ...
Modeling Biological Systems from Heterogeneous Data

Bernard, Allister P. (2008-04-24)

The past decades have seen rapid development of numerous high-throughput technologies to observe biomolecular phenomena. High-throughput biological data are inherently heterogeneous, providing information at the various ...