2 citations · 6 across the 3 of their papers we have counts for
3 papers
stat.ML2019★ 2 cited
Posterior Distribution for the Number of Clusters in Dirichlet Process Mixture Models
Chiao-Yu Yang, Eric Xia, Nhat Ho +1
Dirichlet process mixture models (DPMM) play a central role in Bayesian nonparametrics, with applications throughout statistics and machine learning. DPMMs are generally used in cl…
cs.LG2012★ 2 cited
The DLR Hierarchy of Approximate Inference
Michal Rosen-Zvi, Michael I. Jordan, Alan Yuille
We propose a hierarchy for approximate inference based on the Dobrushin, Lanford, Ruelle (DLR) equations. This hierarchy includes existing algorithms, such as belief propagation, a…
math.ST2006★ 2 cited
Comment on "Support Vector Machines with Applications"
Peter L. Bartlett, Michael I. Jordan, Jon D. McAuliffe
Comment on "Support Vector Machines with Applications" [math.ST/0612817]