Difference between revisions of "10-601 GM1"

From Cohen Courses
Jump to navigationJump to search
(Created page with " === Slides === [http://curtis.ml.cmu.edu/w/courses/images/9/9e/Lecture18-GM.pdf Slides in PDF] === Readings === [http://curtis.ml.cmu.edu/w/courses/images/8/89/GM-jordan.p...")
 
Line 11: Line 11:
  
 
* factorization theorem of BN
 
* factorization theorem of BN
* local conditional dependencies in a BN
+
* Full, independent and intermediate conditional probability models
* directed and undirected GM: BN versus MRF
+
* Markov blanket
* draw HMM and Topic Models as graphical models
+
* Learning a BN
 +
* Inference in BN is NP hard
 +
* Approximate inference in BN

Revision as of 10:09, 12 August 2014

Slides

Slides in PDF

Readings

Graphical Models by Michael I. Jordan

Taking home message

  • factorization theorem of BN
  • Full, independent and intermediate conditional probability models
  • Markov blanket
  • Learning a BN
  • Inference in BN is NP hard
  • Approximate inference in BN