Parameter Estimation for the Latent Dirichlet Allocation
published: Oct. 30, 2013, recorded: October 2013, views: 4833
Report a problem or upload filesIf you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
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.
Download slides: sikdd2013_speh_dirichlet_allocation_01.pdf (289.3 KB)
Link this pageWould you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !