Scaling laws for learning high-dimensional Markov forest distributions

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 structurally consistent and the error probability of structure learn...

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Bibliographic Details
Main Authors: Willsky, Alan S. (Contributor), Tan, Vincent Yan Fu (Contributor), Anandkumar, Animashree (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: Institute of Electrical and Electronics Engineers (IEEE), 2012-10-04T13:43:41Z.
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