On equivalent parameter learning in simplified feature space based on Bayesian asymptotic analysis.
Keisuke YamazakiPublished in: Neural Networks (2012)
Keyphrases
- parameter learning
- asymptotic analysis
- bayesian networks
- feature space
- maximum likelihood
- structure learning
- fluid model
- statistical learning
- conditional random fields
- parameter estimation
- generative model
- posterior probability
- approximate inference
- dimensionality reduction
- em algorithm
- high dimensional
- expectation maximization
- markov random field
- training set
- graphical models
- conditional independence
- posterior distribution
- hidden variables
- probabilistic model
- low dimensional
- probabilistic inference
- data points
- model selection
- bayesian inference
- markov networks
- special case
- stochastic model
- prior knowledge
- feature selection