3 citations · 5 across the 6 of their papers we have counts for
6 papers
Refined Causal Graph Structure Learning via Curvature for Brain Disease Classification
Falih Gozi Febrinanto, Adonia Simango, Chengpei Xu +4
Graph neural networks (GNNs) have been developed to model the relationship between regions of interest (ROIs) in brains and have shown significant improvement in detecting brain di…
Towards Multimodal Metaphor Understanding: A Chinese Dataset and Model for Metaphor Mapping Identification
Dongyu Zhang, Shengcheng Yin, Jingwei Yu +5
Metaphors play a crucial role in human communication, yet their comprehension remains a significant challenge for natural language processing (NLP) due to the cognitive complexity…
FairGP: A Scalable and Fair Graph Transformer Using Graph Partitioning
Renqiang Luo, Huafei Huang, Ivan Lee +3
Recent studies have highlighted significant fairness issues in Graph Transformer (GT) models, particularly against subgroups defined by sensitive features. Additionally, GTs are co…
Millimeter Wave Radar-based Human Activity Recognition for Healthcare Monitoring Robot
Zhanzhong Gu, Xiangjian He, Gengfa Fang +3
Healthcare monitoring is crucial, especially for the daily care of elderly individuals living alone. It can detect dangerous occurrences, such as falls, and provide timely alerts t…
Robot-As-A-Sensor: Forming a Sensing Network with Robots for Underground Mining Missions
Xiaoyu Ai, Chengpei Xu, Binghao Li +1
Nowadays, robots are deployed as mobile platforms equipped with sensing, communication and computing capabilities, especially in the mining industry, where they perform tasks in ha…
Algorithmic Fairness: A Tolerance Perspective
Renqiang Luo, Tao Tang, Feng Xia +5
Recent advancements in machine learning and deep learning have brought algorithmic fairness into sharp focus, illuminating concerns over discriminatory decision making that negativ…