Emergent Mind

Algorithms of the LDA model [REPORT]

(1307.0317)
Published Jul 1, 2013 in cs.LG , cs.IR , and stat.ML

Abstract

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.

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