Scalable Marginal Likelihood Estimation for Model Selection in Deep Learning.
Alexander ImmerMatthias BauerVincent FortuinGunnar RätschMohammad Emtiyaz KhanPublished in: CoRR (2021)
Keyphrases
- model selection
- marginal likelihood
- deep learning
- unsupervised learning
- parameter estimation
- machine learning
- cross validation
- hyperparameters
- selection criterion
- information criterion
- model selection criteria
- sample size
- feature selection
- regression model
- leave one out cross validation
- mixture model
- gaussian process
- data sets
- bayesian information criterion
- generalization error
- variable selection
- approximate inference
- bayesian methods
- posterior distribution
- closed form