2019
Sketching for Latent Dirichlet-Categorical Models
AISTATS 2019poster
Recent work has explored transforming data sets into smaller, approximate summaries in order to scale Bayesian inference. We examine a related problem in which the parameters of a Bayesian model are very large and expensive to store in memory, and propose more compact representations of parameter v…