Expectation propagation for neural networks with sparsity-promoting priors.
Pasi JylänkiAapo NummenmaaAki VehtariPublished in: J. Mach. Learn. Res. (2014)
Keyphrases
- expectation propagation
- neural network
- gaussian process
- gaussian process classification
- bayesian inference
- approximate inference
- density estimation
- bayesian framework
- prior information
- variational bayes
- prior distribution
- bayesian methods
- prior knowledge
- posterior distribution
- free energy
- multilayer perceptron
- graphical models
- competitive learning
- sparse representation
- hyperparameters
- latent variables
- probabilistic inference
- belief propagation
- gaussian mixture model
- parameter estimation
- mixture model
- model selection
- semi supervised
- information extraction
- dynamic programming
- high dimensional
- training set