Large Scale Variational Inference and Experimental Design for Sparse Generalized Linear Models.
Matthias W. SeegerHannes NickischPublished in: Sampling-based Optimization in the Presence of Uncertainty (2009)
Keyphrases
- generalized linear models
- experimental design
- variational inference
- dirichlet process
- regression model
- gaussian process
- bayesian inference
- posterior distribution
- topic models
- probabilistic model
- probabilistic graphical models
- sample size
- active learning
- variational methods
- mixture model
- latent dirichlet allocation
- model selection
- hyperparameters
- closed form
- feature selection
- gaussian processes
- graphical models
- exponential family
- multi task learning
- approximate inference
- exact inference
- prior information
- probability distribution
- latent variables
- high dimensional