A Stochastic Variational Framework for Fitting and Diagnosing Generalized Linear Mixed Models
A Stochastic Variational Framework for Fitting and Diagnosing Generalized Linear Mixed Models
In stochastic variational inference, the variational Bayes objective function is optimized using stochastic gradient approximation, where gradients computed on small random subsets of data are used to approximate the true gradient over the whole data set. This enables complex models to be fit to large data sets as data can …