log-linear MRFs

(50 minutes to learn)


Often, when we use MRFs, we want to assign a particular functional form to the cliques. A common choice is a log-linear representation, where the potentials are log-linear functions of the model parameters. Boltzmann machines and Gaussian MRFs are probably the most common examples.


This concept has the prerequisites:

Core resources (read/watch one of the following)


Coursera: Probabilistic Graphical Models (2013)
An online course on probabilistic graphical models.
Author: Daphne Koller
Additional dependencies:
  • conditional random fields
Other notes:
  • Click on "Preview" to see the videos.


Supplemental resources (the following are optional, but you may find them useful)


See also

-No Additional Notes-