搜索结果: 1-10 共查到“mixture models”相关记录10条 . 查询时间(0.077 秒)
Quantum Annealing for Dirichlet Process Mixture Models with Applications to Network Clustering
Quantum annealing Dirichlet process Stochastic optimization Maximum a posteriori estimation Bayesian nonparametrics
2013/6/17
We developed a new quantum annealing (QA) algorithm for Dirichlet process mixture (DPM) models based on the Chinese restaurant process (CRP). QA is a parallelized extension of simulated annealing (SA)...
PReMiuM: An R Package for Profile Regression Mixture Models using Dirichlet Processes
Profile regression Clustering Dirichlet process mixture model
2013/4/27
PReMiuM is a recently developed R package for Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, non-parametrically linking a response vect...
Capturing Patterns via Parsimonious t Mixture Models
Factor analysis Facial representation Image compression PGMM PTMM
2013/4/27
his paper exploits a simplified version of the mixture of multivariate t-factor analyzers (MtFA) for robust mixture modelling and clustering of high-dimensional data that frequently contain a number o...
Bayesian Mixture Models for Frequent Itemset Discovery
Bayesian Mixture Models Frequent Itemset Discovery
2012/11/26
In binary-transaction data-mining, traditional frequent itemset mining often produces results which are not straightforward to interpret. To overcome this problem, probability models are often used to...
Mixture Models for Single Cell Assays with Applications to Vaccine Studies
Mixture Models Single Cell Assays Applications to Vaccine Studies
2012/9/18
Blood and tissue are composed of many functionally distinct cell subsets. In immunological studies, these can only be measured accurately using single-cell assays. The characterization of these small ...
We present the multidimensional membership mixture (M3) models where every dimension of the membership represents an independent mixture model and each
data point is generated from the selected mixtu...
Finite mixture models with predictive recursion marginal likelihood
Density estimation Dirichlet distribution mixture com-plexity
2011/7/6
Estimation of finite mixture models when the mixing distribution support is unknown is an important and challenging problem. In this paper, a new approach is given based on the recently proposed predi...
Semiparametric inference in mixture models with predictive recursion marginal likelihood
Density estimation Dirichlet process mixture empirical Bayes filtering algorithm
2011/7/5
Predictive recursion is an accurate and computationally efficient algorithm for nonparametric estimation of mixing densities in mixture models. In semiparametric mixture models, however, the algorithm...
Spades and Mixture Models
Adaptive estimation aggregation lasso minimax risk mixturemodels consistent model selection
2010/3/17
This paper studies sparse density estimation via ℓ1 penalization (SPADES).We
focus on estimation in high-dimensional mixture models and nonparametric adaptive density
estimation. We show, resp...
An Overview of Mixture Models
Bayesian methods bootstrapping identifiability EM algorithm label switching
2010/4/30
With the advancement of statistical theory and computing
power, data sets are providing a greater amount of insight into the problems
of today. Statisticians have an ever increasing number of tools ...