Exploiting Compositionality to Explore a Large Space of Model Structures

Exploiting Compositionality to Explore a Large Space of Model Structures

The recent proliferation of richly structured probabilistic models raises the question of how to automatically determine an appropriate model for a dataset. We investigate this question for a space of matrix decomposition models which can express a variety of widely used models from unsupervised lea...

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Bibliographic Details
Main Authors: Grosse, Roger Baker (Contributor), Salakhutdinov, Ruslan (Author), Freeman, William T. (Contributor), Tenenbaum, Joshua B. (Contributor)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor), Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor)
Format: Article
Language:English
Published: AUAI Press, 2014-04-23T16:23:51Z.
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