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NIPS
2004

Exponential Family Harmoniums with an Application to Information Retrieval

9 years 1 months ago
Exponential Family Harmoniums with an Application to Information Retrieval
Directed graphical models with one layer of observed random variables and one or more layers of hidden random variables have been the dominant modelling paradigm in many research fields. Although this approach has met with considerable success, the causal semantics of these models can make it difficult to infer the posterior distribution over the hidden variables. In this paper we propose an alternative two-layer model based on exponential family distributions and the semantics of undirected models. Inference in these "exponential family harmoniums" is fast while learning is performed by minimizing contrastive divergence. A member of this family is then studied as an alternative probabilistic model for latent semantic indexing. In experiments it is shown that they perform well on document retrieval tasks and provide an elegant solution to searching with keywords.
Max Welling, Michal Rosen-Zvi, Geoffrey E. Hinton
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where NIPS
Authors Max Welling, Michal Rosen-Zvi, Geoffrey E. Hinton
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