Difference between revisions of "10-601 GM2"
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| + | This a lecture used in the [[Syllabus for Machine Learning 10-601B in Spring 2016]] | ||
=== Slides === | === Slides === | ||
| − | [http:// | + | * [http://www.cs.cmu.edu/~wcohen/10-601/networks-2.pptx Slides in PPT], [http://www.cs.cmu.edu/~wcohen/10-601/networks-2.pdf Slides in PDF]. |
=== Readings === | === Readings === | ||
| − | * [ | + | * See [[10-601 GM1|previous lecture]] |
| − | + | ||
| − | |||
=== To remember === | === To remember === | ||
Latest revision as of 10:52, 31 March 2016
This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016
Slides
Readings
- See previous lecture
To remember
- what is inference in DGMs
- the general outline of the BP algorithm for polytrees
- what is a polytree and when is BP exact
- what "message passing" means
- what a Markov blanket is
- what a Markov network (undirected model) is
- how node can be merged to create a polytree
- the advantages and disadvantages of BP on polytrees and loopy BP
