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Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture
Dynamic Clustering Asymptotics Dependent Dirichlet Process Mixture
2013/6/17
This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters. The alg...
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)...
Splitting and Merging Components of a Nonconjugate Dirichlet Process Mixture Model
Bayesian model Markov chain Monte Carlo split-merge moves nonconjugate prior
2009/9/22
The inferential problem of associating data to mixture components is dif-
ficult when components are nearby or overlapping. We introduce a new split-merge
Markov chain Monte Carlo technique that eff...
Mean field inference for the Dirichlet process mixture model
Bayesian nonparametrics approximation methods variational inference density estimation
2009/9/16
We present a systematic study of several recently proposed methods of mean field inference for the Dirichlet process mixture (DPM) model. These methods provide approximations to the posterior distribu...