4 citations · 12 across the 9 of their papers we have counts for
9 papers
Back to Prior Knowledge: Joint Event Causality Extraction via Convolutional Semantic Infusion
Zijian Wang, Hao Wang, Xiangfeng Luo +1
Joint event and causality extraction is a challenging yet essential task in information retrieval and data mining. Recently, pre-trained language models (e.g., BERT) yield state-of…
A Targeted Universal Attack on Graph Convolutional Network
Jiazhu Dai, Weifeng Zhu, Xiangfeng Luo
Graph-structured data exist in numerous applications in real life. As a state-of-the-art graph neural network, the graph convolutional network (GCN) plays an important role in proc…
Emotion Correlation Mining Through Deep Learning Models on Natural Language Text
Xinzhi Wang, Luyao Kou, Vijayan Sugumaran +2
Emotion analysis has been attracting researchers' attention. Most previous works in the artificial intelligence field focus on recognizing emotion rather than mining the reason why…
Enhancing Relation Extraction Using Syntactic Indicators and Sentential Contexts
Qiongxing Tao, Xiangfeng Luo, Hao Wang
State-of-the-art methods for relation extraction consider the sentential context by modeling the entire sentence. However, syntactic indicators, certain phrases or words like prepo…
Proximal Policy Optimization with Mixed Distributed Training
Zhenyu Zhang, Xiangfeng Luo, Tong Liu +5
Instability and slowness are two main problems in deep reinforcement learning. Even if proximal policy optimization (PPO) is the state of the art, it still suffers from these two p…
Dependent Indian Buffet Process-based Sparse Nonparametric Nonnegative Matrix Factorization
Junyu Xuan, Jie Lu, Guangquan Zhang +2
Nonnegative Matrix Factorization (NMF) aims to factorize a matrix into two optimized nonnegative matrices appropriate for the intended applications. The method has been widely used…