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Parameter Estimation for the Latent Dirichlet Allocation

Parameter Estimation for the Latent Dirichlet Allocation

This video was recorded at Slovenian KDD Conference on Data Mining and Data Warehouses (SiKDD), Ljubljana 2013. We review three algorithms for parameter estimation of the Latent Dirichlet Allocation model: batch variational Bayesian inference, online variational Bayesian inference and inference using collapsed Gibbs sampling. We experimentally compare their time complexity and performance. We find that the online variational Bayesian inference converges faster than the other two inference techniques, with comparable quality of the results.


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