10-601 Topic Models
From Cohen Courses
This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016
Poll: https://piazza.com/class/ij382zqa2572hc
Slides
Readings
- Murphy ch 27.3 (don't read 27.3.6) and 27.4.
- LDA is not covered in Mitchell. There's a nice overview paper on LDA by David Blei.
- Here's the code I discussed in class and some sample data.
- The Dirichlet-multinomial page on wikipedia has a good discussion of collapsed Gibbs sampling.
Summary
You should know:
- what Gibbs sampling is, and how it can be used for inference in a directed graphical model.
- what graphical models are associated with supervised naive Bayes, unsupervised naive Bayes, and LDA.
