ICASSP
2011
IEEE
13 years 3 months ago
2011
IEEE
The Dirichlet Process Mixture (DPM) models represent an attractive approach to modeling latent distributions parametrically. In DPM models the Dirichlet process (DP) is applied es...
JMLR
2010
13 years 6 months ago
2010
We are concerned with a multivariate response regression problem where the interest is in considering correlations both across response variates and across response samples. In th...
JMLR
2010
13 years 6 months 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 ...
JMLR
2010
13 years 6 months ago
2010
A non-parametric hierarchical Bayesian framework is developed for designing a classifier, based on a mixture of simple (linear) classifiers. Each simple classifier is termed a loc...
TSP
2011
13 years 6 months ago
2011
—Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
JCST
2010
13 years 10 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...
IJCV
2008
13 years 11 months ago
2008
Image segmentation algorithms partition the set of pixels of an image into a specific number of different, spatially homogeneous groups. We propose a nonparametric Bayesian model f...
ICML
2010
IEEE
14 years 15 days ago
2010
IEEE
The hierarchical Dirichlet process (HDP) is a Bayesian nonparametric mixed membership model--each data point is modeled with a collection of components of different proportions. T...
ICML
2010
IEEE
14 years 15 days ago
2010
IEEE
We present a probabilistic model for clustering of objects represented via pairwise dissimilarities. We propose that even if an underlying vectorial representation exists, it is b...
ICPR
2010
IEEE
14 years 3 months ago
2010
IEEE
—In Dirichlet process (DP) mixture models, the number of components is implicitly determined by the sampling parameters of Dirichlet process. However, this kind of models usually...