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CVPR
2005
IEEE
14 years 6 months ago
Mixture Trees for Modeling and Fast Conditional Sampling with Applications in Vision and Graphics
We introduce mixture trees, a tree-based data-structure for modeling joint probability densities using a greedy hierarchical density estimation scheme. We show that the mixture tr...
Frank Dellaert, Vivek Kwatra, Sang Min Oh
BMCBI
2008
107views more  BMCBI 2008»
13 years 4 months ago
A mixture model approach to sample size estimation in two-sample comparative microarray experiments
Background: Choosing the appropriate sample size is an important step in the design of a microarray experiment, and recently methods have been proposed that estimate sample sizes ...
Tommy S. Jørstad, Herman Midelfart, Atle M....
BMCBI
2011
12 years 8 months ago
A Beta-Mixture Model for Dimensionality Reduction, Sample Classification and Analysis
Background: Patterns of genome-wide methylation vary between tissue types. For example, cancer tissue shows markedly different patterns from those of normal tissue. In this paper ...
Kirsti Laurila, Bodil Oster, Claus L. Andersen, Ph...
ICPR
2010
IEEE
13 years 8 months ago
CDP Mixture Models for Data Clustering
—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...
Yangfeng Ji, Tong Lin, Hongbin Zha
ICML
2007
IEEE
14 years 5 months ago
A permutation-augmented sampler for DP mixture models
We introduce a new inference algorithm for Dirichlet process mixture models. While Gibbs sampling and variational methods focus on local moves, the new algorithm makes more global...
Percy Liang, Michael I. Jordan, Benjamin Taskar