14 citations · 34 across the 8 of their papers we have counts for
8 papers
Co-Regularized Adversarial Learning for Multi-Domain Text Classification
Yuan Wu, Diana Inkpen, Ahmed El-Roby
Multi-domain text classification (MDTC) aims to leverage all available resources from multiple domains to learn a predictive model that can generalize well on these domains. Recent…
Maximum Batch Frobenius Norm for Multi-Domain Text Classification
Yuan Wu, Diana Inkpen, Ahmed El-Roby
Multi-domain text classification (MDTC) has obtained remarkable achievements due to the advent of deep learning. Recently, many endeavors are devoted to applying adversarial learni…
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.…
CBench: Towards Better Evaluation of Question Answering Over Knowledge Graphs
Abdelghny Orogat, Isabelle Liu, Ahmed El-Roby
Recently, there has been an increase in the number of knowledge graphs that can be only queried by experts. However, describing questions using structured queries is not straightfo…
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…
Dual Mixup Regularized Learning for Adversarial Domain Adaptation
Yuan Wu, Diana Inkpen, Ahmed El-Roby
Recent advances on unsupervised domain adaptation (UDA) rely on adversarial learning to disentangle the explanatory and transferable features for domain adaptation. However, there…
Sapphire: Querying RDF Data Made Simple
Ahmed El-Roby, Khaled Ammar, Ashraf Aboulnaga +1
RDF data in the linked open data (LOD) cloud is very valuable for many different applications. In order to unlock the full value of this data, users should be able to issue complex…