Learning Latent Tree Graphical Models
We study the problem of learning a latent tree graphical model where samples are available only from a subset of variables. We propose two consistent and computationally efficient algorithms for learning minimal latent trees, that is, trees without any redundant hidden nodes. Unlike many existing me...
Main Authors: | Choi, Myung Jin, Willsky, Alan S., Tan, Vincent Y. F., Anandkumar, Animashree |
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Other Authors: | Massachusetts Institute of Technology. Laboratory for Information and Decision Systems |
Format: | Article |
Language: | en_US |
Published: |
CrossRef test prefix
2012
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Online Access: | http://hdl.handle.net/1721.1/71241 https://orcid.org/0000-0003-0149-5888 |
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