Density-Preserving Hierarchical EM Algorithm: Simplifying Gaussian Mixture Models for Approximate Inference.
Lei YuTianyu YangAntoni B. ChanPublished in: IEEE Trans. Pattern Anal. Mach. Intell. (2019)
Keyphrases
- approximate inference
- em algorithm
- gaussian mixture model
- parameter estimation
- expectation maximization
- mixture model
- probability density
- graphical models
- maximum likelihood
- gaussian process
- exact inference
- hyperparameters
- belief propagation
- maximum likelihood estimation
- generative model
- probabilistic model
- gaussian mixture
- probability density function
- probabilistic inference
- latent variables
- message passing
- maximum a posteriori
- posterior distribution
- markov chain monte carlo
- gaussian distribution
- density function
- unsupervised learning
- structured prediction
- variational bayes
- density estimation
- likelihood function
- log likelihood
- random variables
- free energy
- conditional random fields
- finite mixtures
- incomplete data
- reinforcement learning
- model selection