Learning high-dimensional Markov forest distributions: Analysis of error rates

The problem of learning forest-structured discrete graphical models from i.i.d. samples is considered. An algorithm based on pruning of the Chow-Liu tree through adaptive thresholding is proposed. It is shown that this algorithm is both structurally consistent and risk consistent and the error proba...

Full description

Bibliographic Details
Main Authors: Tan, Vincent Yan Fu (Contributor), Anandkumar, Animashree (Author), Willsky, Alan S. (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: MIT Press, 2011-10-20T15:01:40Z.
Subjects:
Online Access:Get fulltext