Sampling for Bayesian Mixture Models: MCMC with Polynomial-Time Mixing.
Wenlong MouNhat HoMartin J. WainwrightPeter L. BartlettMichael I. JordanPublished in: CoRR (2019)
Keyphrases
- mixture model
- markov chain monte carlo
- generative model
- posterior probability
- posterior distribution
- probabilistic model
- parameter estimation
- em algorithm
- sampling algorithm
- bayesian inference
- gaussian mixture model
- expectation maximization
- maximum likelihood
- monte carlo
- markov chain
- bayesian framework
- density estimation
- model selection
- probability density function
- language model
- gibbs sampling
- metropolis hastings algorithm
- exponential family
- dirichlet process
- dirichlet prior
- bayesian networks
- latent dirichlet allocation
- mixture modeling
- discriminative learning
- proposal distribution
- probability distribution
- prior distribution
- topic models
- prior knowledge
- unsupervised learning
- approximate inference
- gaussian mixture
- finite mixtures
- automatic model selection
- bayesian model
- text classification
- semi supervised
- gaussian distribution
- model based clustering
- computer vision
- generalized em algorithm