Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process.
Michael C. HughesDae Il KimErik B. SudderthPublished in: AISTATS (2015)
Keyphrases
- variational inference
- hierarchical dirichlet process
- bayesian inference
- topic models
- posterior distribution
- mixture model
- gaussian process
- probabilistic graphical models
- latent dirichlet allocation
- variational methods
- probabilistic model
- hidden markov models
- closed form
- exponential family
- dirichlet process
- exact inference
- unsupervised manner
- graphical models
- latent variables
- bayesian model
- bayesian framework
- gaussian processes
- factor graphs
- density estimation
- maximum a posteriori
- latent topics
- hyperparameters
- optic flow
- level set
- model selection
- approximate inference
- generative model
- maximum likelihood
- em algorithm
- machine learning
- missing values
- gaussian mixture model