  We review three algorithms for Latent Dirichlet Allocation (LDA). Two of them
are variational inference algorithms: Variational Bayesian inference and Online
Variational Bayesian inference and one is Markov Chain Monte Carlo (MCMC)
algorithm -- Collapsed Gibbs sampling. We compare their time complexity and
performance. We find that online variational Bayesian inference is the fastest
algorithm and still returns reasonably good results.
