5 citations · 8 across the 2 of their papers we have counts for
2 papers
stat.ML2017★ 5 cited
GALILEO: A Generalized Low-Entropy Mixture Model
Cetin Savkli, Jeffrey Lin, Philip Graff +1
We present a new method of generating mixture models for data with categorical attributes. The keys to this approach are an entropy-based density metric in categorical space and an…
cs.LG2017★ 3 cited
Bayesian Learning of Clique Tree Structure
Cetin Savkli, J. Ryan Carr, Philip Graff +1
The problem of categorical data analysis in high dimensions is considered. A discussion of the fundamental difficulties of probability modeling is provided, and a solution to the d…