Few-Shot Transfer Learning for Text Classification With Lightweight Word Embedding Based Models
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DOI: 10.1109/access.2019.2911850
Abstract: Many deep learning architectures have been employed to model the semantic compositionality for text sequences, requiring a huge amount of supervised data for parameters training, making it unfeasible in situations where numerous annotated samples are… read more here.
Keywords: shot transfer; based models; embedding based; transfer learning ... See more keywords