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Original paper

Aspect-augmented Adversarial Networks for Domain Adaptation

Volume: 5, Pages: 515 - 528
Published: Dec 1, 2017
Abstract
We introduce a neural method for transfer learning between two (source and target) classification tasks or aspects over the same domain. Rather than training on target labels, we use a few keywords pertaining to source and target aspects indicating sentence relevance instead of document class labels. Documents are encoded by learning to embed and softly select relevant sentences in an aspect-dependent manner. A shared classifier is trained on...
Paper Details
Title
Aspect-augmented Adversarial Networks for Domain Adaptation
Published Date
Dec 1, 2017
Volume
5
Pages
515 - 528
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