1.2k citations · 1.5k across the 11 of their papers we have counts for
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Towards Category and Domain Alignment: Category-Invariant Feature Enhancement for Adversarial Domain Adaptation
Yuan Wu, Diana Inkpen, Ahmed El-Roby
Adversarial domain adaptation has made impressive advances in transferring knowledge from the source domain to the target domain by aligning feature distributions of both domains.…
Context-Sensitive Visualization of Deep Learning Natural Language Processing Models
Andrew Dunn, Diana Inkpen, Răzvan Andonie
The introduction of Transformer neural networks has changed the landscape of Natural Language Processing (NLP) during the last years. So far, none of the visualization systems has…
Conditional Adversarial Networks for Multi-Domain Text Classification
Yuan Wu, Diana Inkpen, Ahmed El-Roby
In this paper, we propose conditional adversarial networks (CANs), a framework that explores the relationship between the shared features and the label predictions to impose more d…
Mixup Regularized Adversarial Networks for Multi-Domain Text Classification
Yuan Wu, Diana Inkpen, Ahmed El-Roby
Using the shared-private paradigm and adversarial training has significantly improved the performances of multi-domain text classification (MDTC) models. However, there are two iss…