26 citations · 47 across the 4 of their papers we have counts for
4 papers
Hierarchical Taxonomy-Aware and Attentional Graph Capsule RCNNs for Large-Scale Multi-Label Text Classification
Hao Peng, Jianxin Li, Qiran Gong +5
CNNs, RNNs, GCNs, and CapsNets have shown significant insights in representation learning and are widely used in various text mining tasks such as large-scale multi-label text clas…
Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks
Hao Peng, Jianxin Li, Qiran Gong +4
Events are happening in real-world and real-time, which can be planned and organized occasions involving multiple people and objects. Social media platforms publish a lot of text m…
Dynamic Network Embedding via Incremental Skip-gram with Negative Sampling
Hao Peng, Jianxin Li, Hao Yan +5
Network representation learning, as an approach to learn low dimensional representations of vertices, has attracted considerable research attention recently. It has been proven ext…
Graph Convolutional Neural Networks via Motif-based Attention
Hao Peng, Jianxin Li, Qiran Gong +3
Many real-world problems can be represented as graph-based learning problems. In this paper, we propose a novel framework for learning spatial and attentional convolution neural ne…