252 citations · 616 across the 34 of their papers we have counts for
9 papers · 1 filter
HETFORMER: Heterogeneous Transformer with Sparse Attention for Long-Text Extractive Summarization
Ye Liu, Jian-Guo Zhang, Yao Wan +3
To capture the semantic graph structure from raw text, most existing summarization approaches are built on GNNs with a pre-trained model. However, these methods suffer from cumbers…
Multi-level Feature Learning for Contrastive Multi-view Clustering
Jie Xu, Huayi Tang, Yazhou Ren +3
Multi-view clustering can explore common semantics from multiple views and has attracted increasing attention. However, existing works punish multiple objectives in the same featur…
A Robust and Generalized Framework for Adversarial Graph Embedding
Jianxin Li, Xingcheng Fu, Hao Peng +5
Graph embedding is essential for graph mining tasks. With the prevalence of graph data in real-world applications, many methods have been proposed in recent years to learn high-qua…
Error-Robust Multi-View Clustering: Progress, Challenges and Opportunities
Mehrnaz Najafi, Lifang He, Philip S. Yu
With recent advances in data collection from multiple sources, multi-view data has received significant attention. In multi-view data, each view represents a different perspective…
Graph Entropy Guided Node Embedding Dimension Selection for Graph Neural Networks
Gongxu Luo, Jianxin Li, Jianlin Su +5
Graph representation learning has achieved great success in many areas, including e-commerce, chemistry, biology, etc. However, the fundamental problem of choosing the appropriate…
Non-Linear Fusion for Self-Paced Multi-View Clustering
Zongmo Huang, Yazhou Ren, Xiaorong Pu +1
With the advance of the multi-media and multi-modal data, multi-view clustering (MVC) has drawn increasing attentions recently. In this field, one of the most crucial challenges is…
Higher-Order Attribute-Enhancing Heterogeneous Graph Neural Networks
Jianxin Li, Hao Peng, Yuwei Cao +4
Graph neural networks (GNNs) have been widely used in deep learning on graphs. They can learn effective node representations that achieve superior performances in graph analysis ta…
Streaming Social Event Detection and Evolution Discovery in Heterogeneous Information Networks
Hao Peng, Jianxin Li, Yangqiu Song +4
Events are happening in real-world and real-time, which can be planned and organized for occasions, such as social gatherings, festival celebrations, influential meetings or sports…
Self-Supervised Discriminative Feature Learning for Deep Multi-View Clustering
Jie Xu, Yazhou Ren, Huayi Tang +6
Multi-view clustering is an important research topic due to its capability to utilize complementary information from multiple views. However, there are few methods to consider the…