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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...
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...
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 ...