1.8k citations · 4k across the 38 of their papers we have counts for
3 papers · 1 filter
Sparse Stochastic Inference for Latent Dirichlet allocation
David Mimno, Matt Hoffman, David Blei
We present a hybrid algorithm for Bayesian topic models that combines the efficiency of sparse Gibbs sampling with the scalability of online stochastic inference. We used our algor…
Nonparametric variational inference
Samuel Gershman, Matt Hoffman, David Blei
Variational methods are widely used for approximate posterior inference. However, their use is typically limited to families of distributions that enjoy particular conjugacy proper…
Stochastic Variational Inference
Matt Hoffman, David M. Blei, Chong Wang +1
We develop stochastic variational inference, a scalable algorithm for approximating posterior distributions. We develop this technique for a large class of probabilistic models and…