Learning loosely connected Markov random fields
We consider the structure learning problem for graphical models that we call loosely connected Markov random fields, in which the number of short paths between any pair of nodes is small, and present a new conditional independence test based algorithm for learning the underlying graph structure. The...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Institute for Operations Research and the Management Sciences (INFORMS)
2014-01-01
|
| Series: | Stochastic Systems |
| Subjects: | |
| Online Access: | http://www.i-journals.org/ssy/viewarticle.php?id=73&layout=abstract |