Stochastic Gaussian Process Model Averaging for High-Dimensional Inputs.
Maxime XuerebSzu Hui NgGiulia PedrielliPublished in: WSC (2020)
Keyphrases
- gaussian process
- model averaging
- high dimensional
- posterior distribution
- hyperparameters
- gaussian processes
- bayesian methods
- model selection
- bayesian framework
- latent variables
- cross validation
- semi supervised
- parameter space
- low dimensional
- regression model
- approximate inference
- dimensionality reduction
- expectation propagation
- support vector
- closed form
- sample size
- em algorithm
- marginal likelihood
- bayesian inference
- maximum likelihood
- random sampling
- maximum a posteriori
- noise level
- prior information
- high dimensional data
- probability distribution
- incomplete data
- learning algorithm
- generative model
- feature selection