INFO 6150

INFO 6150

Course information provided by the Courses of Study 2018-2019.

Statistical topic models such as LDA provide a powerful tool for discovering themes in large unlabeled text corpora. They are increasingly popular in a wide range of fields, both as a data-driven alternative to manual document coding methods, and also as an example of a difficult but tractable problem in statistical inference. This course will cover Bayesian model construction, inference techniques, evaluation, and applications beyond text such as community detection in networks and population admixture in genetics.

When Offered Fall.

Permission Note Enrollment limited to: graduate students or seniors.
Prerequisites/Corequisites Prerequisite: familiarity with Bayesian statistics and probabilistic modeling.

View Enrollment Information

Syllabi: none
  •   Regular Academic Session.  Combined with: CS 6788

  • 3 Credits Graded

  • 16815 INFO 6150   SEM 101