Parameter Estimation in Gamma Mixture Model using Normal-based Approximation.
R. Vani LakshmiV. S. VaidyanathanPublished in: J. Stat. Theory Appl. (2016)
Keyphrases
- parameter estimation
- mixture model
- em algorithm
- model selection
- expectation maximization
- maximum likelihood
- gaussian mixture model
- density estimation
- statistical models
- maximum likelihood estimation
- generative model
- parameter estimation algorithm
- unsupervised learning
- probabilistic model
- approximate inference
- language model
- hyperparameters
- probability density function
- closed form
- maximum a posteriori
- posterior distribution
- gaussian mixture
- gibbs sampling
- image segmentation
- markov random field
- gaussian distribution
- least squares
- likelihood function
- bayesian framework
- density function
- supervised learning
- feature vectors
- high dimensional
- feature space
- markov chain monte carlo
- image sequences
- variational inference
- machine learning
- probabilistic mixture model