INFO 6150

Advanced Topic Modeling

Course Description

Course information provided by the 2016-2017 Catalog.

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.

Prerequisites/Corequisites Prerequisite: familiarity with Bayesian statistics and probabilistic modeling.

Permission Note Erollment limited to: graduate students or seniors.

When Offered Fall.

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