Eisenstein et al 2011: Sparse Additive Generative Models of Text

Citation

Sparse Additive Generative Models of Text. Eisenstein, Ahmed and Xing. Proceedings of ICML 2011.

Online version

Eisenstein et al 2011

Summary

This paper presents sparse learning and additive generative modeling approaches for , which is an alternative training method for general problems in Probabilistic Graphical Models (e.g. possible applications include , , , and ).

Brief Description of the method

This paper first formulates the problem as xxx, then discusses the use of and the use of xxx to. In this section, we will first summarize the method they use

Dataset and Experiment Settings

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Experimental Results

The authors performed three major experiments. The first experiment is the . The second experiment explores.

Exp

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Exp

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Related Papers

This paper is related to many papers in three dimensions.

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