Papers with discriminative labeler

1 papers
Variational Sequential Labelers for Semi-Supervised Learning (D18-1)

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Challenge: a family of multitask variational methods for semi-supervised sequence labeling is currently unclear how to use them in the context of sequence labelling.
Approach: They propose a family of multitask variational methods for semi-supervised sequence labeling using latent variables and a discriminative labeler.
Outcome: The proposed models outperform standard sequential baselines on 8 sequence labeling datasets and improve further with unlabeled data.

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