ALBU: An approximate Loopy Belief message passing algorithm for LDA to improve performance on small data sets. (arXiv:2110.00635v2 [cs.LG] UPDATED)

Variational Bayes (VB) applied to latent Dirichlet allocation (LDA) has
become the most popular algorithm for aspect modeling. While sufficiently
successful in text topic extraction from large corpora, VB is less successful
in identifying aspects in the presence of limited data. We present a novel
variational message passing algorithm as applied to Latent Dirichlet Allocation
(LDA) and compare it with the gold standard VB and collapsed Gibbs sampling. In
situations where marginalisation leads to non-conjugate messages, we use ideas
from …

algorithm arxiv belief data data sets lda lg performance small small data