A review of undirected and acyclic directed Gaussian Markov model selection and estimation.
Irene Córdoba-SánchezConcha BielzaPedro LarrañagaPublished in: CoRR (2016)
Keyphrases
- model selection
- parameter estimation
- error estimation
- cross validation
- selection criterion
- hyperparameters
- bayesian learning
- statistical learning
- sample size
- regression model
- mixture model
- markov chain
- gaussian process
- variable selection
- machine learning
- generalization bounds
- bayesian methods
- generalization error
- model selection criteria
- feature selection
- motion segmentation
- gaussian mixture model
- np hard
- maximum likelihood
- statistical inference
- bayesian information criterion
- information criterion
- marginal likelihood
- density estimation
- conditional independence
- graphical models
- lower bound
- leave one out cross validation