14 citations · 19 across the 3 of their papers we have counts for
5 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…
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…
Dual Adversarial Co-Learning for Multi-Domain Text Classification
Yuan Wu, Yuhong Guo
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 extracti…
Chi-Square Test Neural Network: A New Binary Classifier based on Backpropagation Neural Network
Yuan Wu, Lingling Li, Lian Li
We introduce the chi-square test neural network: a single hidden layer backpropagation neural network using chi-square test theorem to redefine the cost function and the error func…