277 citations · 811 across the 38 of their papers we have counts for
6 papers · 1 filter
Joint Learning of Graph Representation and Node Features in Graph Convolutional Neural Networks
Jiaxiang Tang, Wei Hu, Xiang Gao +1
Graph Convolutional Neural Networks (GCNNs) extend classical CNNs to graph data domain, such as brain networks, social networks and 3D point clouds. It is critical to identify an a…
A Multi-Task Learning Framework for Overcoming the Catastrophic Forgetting in Automatic Speech Recognition
Jiabin Xue, Jiqing Han, Tieran Zheng +2
Recently, data-driven based Automatic Speech Recognition (ASR) systems have achieved state-of-the-art results. And transfer learning is often used when those existing systems are a…
Jointly Optimizing Diversity and Relevance in Neural Response Generation
Xiang Gao, Sungjin Lee, Yizhe Zhang +4
Although recent neural conversation models have shown great potential, they often generate bland and generic responses. While various approaches have been explored to diversify the…
Exploring Structure-Adaptive Graph Learning for Robust Semi-Supervised Classification
Xiang Gao, Wei Hu, Zongming Guo
Graph Convolutional Neural Networks (GCNNs) are generalizations of CNNs to graph-structured data, in which convolution is guided by the graph topology. In many cases where graphs a…
Understanding the Mechanism of Deep Learning Framework for Lesion Detection in Pathological Images with Breast Cancer
Wei-Wen Hsu, Chung-Hao Chen, Chang Hoa +7
The computer-aided detection (CADe) systems are developed to assist pathologists in slide assessment, increasing diagnosis efficiency and reducing missing inspections. Many studies…
Consistent Dialogue Generation with Self-supervised Feature Learning
Yizhe Zhang, Xiang Gao, Sungjin Lee +4
Generating responses that are consistent with the dialogue context is one of the central challenges in building engaging conversational agents. We demonstrate that neural conversat…