Dual Adversarial Co-Learning for Multi-Domain Text Classification
national conference on artificial intelligence, 2020.
In this paper we propose a novel dual adversarial co-learning approach for multi-domain text classification (MDTC). The approach learns shared-private networks for feature extraction and deploys dual adversarial regularizations to align features across different domains and between labeled and unlabeled data simultaneously under a discr...More
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