Transfer Learning for Sequence Labeling Using Source Model and Target Data

14 Feb 2019 Lingzhen Chen Alessandro Moschitti

In this paper, we propose an approach for transferring the knowledge of a neural model for sequence labeling, learned from the source domain, to a new model trained on a target domain, where new label categories appear. Our transfer learning (TL) techniques enable to adapt the source model using the target data and new categories, without accessing to the source data... (read more)

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