• Corpus ID: 570528

A Linear Dynamical System Model for Text

@inproceedings{Belanger2015ALD,
  title={A Linear Dynamical System Model for Text},
  author={David Belanger and Sham M. Kakade},
  booktitle={International Conference on Machine Learning},
  year={2015}
}
Low dimensional representations of words allow accurate NLP models to be trained on limited annotated data. While most representations ignore words' local context, a natural way to induce context-dependent representations is to perform inference in a probabilistic latent-variable sequence model. Given the recent success of continuous vector space word representations, we provide such an inference procedure for continuous states, where words' representations are given by the posterior mean of a… 

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