A framework for parameter estimation and model selection in kernel deep stacking networks.
Thomas WelchowskiMatthias SchmidPublished in: Artif. Intell. Medicine (2016)
Keyphrases
- model selection
- parameter estimation
- cross validation
- bayesian model selection
- hyperparameters
- markov random field
- statistical inference
- maximum likelihood
- parameter estimation algorithm
- em algorithm
- sample size
- least squares
- statistical models
- posterior distribution
- mixture model
- marginal likelihood
- parameter values
- statistical learning
- machine learning
- gaussian process
- support vector
- random fields
- kernel matrix
- regression model
- approximate inference
- selection criterion
- kernel learning
- feature selection
- probabilistic model
- likelihood function
- image processing
- data mining
- model selection criteria