68 search results - page 3 / 14 » Classification with Incomplete Data Using Dirichlet Process ... |
JCST
2010
13 years 4 months ago
2010
In the Bayesian mixture modeling framework it is possible to infer the necessary number of components to model the data and therefore it is unnecessary to explicitly restrict the n...
IJCAI
2007
13 years 7 months ago
2007
Nonparametric Bayesian mixture models, in particular Dirichlet process (DP) mixture models, have shown great promise for density estimation and data clustering. Given the size of ...
ICASSP
2009
IEEE
13 years 9 months ago
2009
IEEE
The Dirichlet process can be used as a nonparametric prior for an infinite-dimensional probability mass function on the parameter space of a mixture model. The set of parameters o...
ICML
2007
IEEE
14 years 6 months ago
2007
IEEE
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
JMLR
2010
13 years 12 days ago
2010
We develop a Bayesian framework for supervised dimension reduction using a flexible nonparametric Bayesian mixture modeling approach. Our method retrieves the dimension reduction ...