A derivation of variational message passing (VMP) for latent Dirichlet allocation (LDA). (arXiv:2111.01480v2 [cs.LG] UPDATED)

Latent Dirichlet Allocation (LDA) is a probabilistic model used to uncover
latent topics in a corpus of documents. Inference is often performed using
variational Bayes (VB) algorithms, which calculate a lower bound to the
posterior distribution over the parameters. Deriving the variational update
equations for new models requires considerable manual effort; variational
message passing (VMP) has emerged as a "black-box" tool to expedite the process
of variational inference. But applying VMP in practice still presents subtle
challenges, and the existing …

arxiv derivation lda lg