Posterior Asymptotics for Boosted Hierarchical Dirichlet Process Mixtures.
Marta CatalanoPierpaolo De BlasiAntonio LijoiIgor PrünsterPublished in: J. Mach. Learn. Res. (2022)
Keyphrases
- hierarchical dirichlet process
- mixture model
- posterior distribution
- probabilistic model
- variational inference
- dirichlet process
- em algorithm
- expectation maximization
- hidden markov models
- gaussian mixture model
- generative model
- variational bayes
- bayesian framework
- unsupervised manner
- density estimation
- probability distribution
- latent variables
- posterior probability
- markov chain
- hyperparameters
- latent dirichlet allocation
- gaussian process
- topic models
- language model
- parameter estimation
- maximum likelihood
- markov chain monte carlo
- model selection
- unsupervised learning
- bayesian model
- sampling algorithm
- graphical models
- bayesian inference
- machine learning
- bayesian networks
- feature selection