Zobrazeno 1 - 10
of 2 167
pro vyhledávání: '"Ma, Xiaojun"'
Autor:
He, Xinyi, Zhou, Mengyu, Xu, Xinrun, Ma, Xiaojun, Ding, Rui, Du, Lun, Gao, Yan, Jia, Ran, Chen, Xu, Han, Shi, Yuan, Zejian, Zhang, Dongmei
Tabular data analysis is crucial in various fields, and large language models show promise in this area. However, current research mostly focuses on rudimentary tasks like Text2SQL and TableQA, neglecting advanced analysis like forecasting and chart
Externí odkaz:
http://arxiv.org/abs/2312.13671
Publikováno v:
Journal of Managerial Psychology, 2024, Vol. 39, Issue 6, pp. 815-831.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/JMP-11-2022-0588
Collaborative filtering (CF) is an important research direction in recommender systems that aims to make recommendations given the information on user-item interactions. Graph CF has attracted more and more attention in recent years due to its effect
Externí odkaz:
http://arxiv.org/abs/2306.03624
Autor:
Yue, Chongjian, Xu, Xinrun, Ma, Xiaojun, Du, Lun, Liu, Hengyu, Ding, Zhiming, Jiang, Yanbing, Han, Shi, Zhang, Dongmei
Large Language Models (LLMs) demonstrate exceptional performance in textual understanding and tabular reasoning tasks. However, their ability to comprehend and analyze hybrid text, containing textual and tabular data, remains underexplored. In this r
Externí odkaz:
http://arxiv.org/abs/2305.16344
Graph Transformer is gaining increasing attention in the field of machine learning and has demonstrated state-of-the-art performance on benchmarks for graph representation learning. However, as current implementations of Graph Transformer primarily f
Externí odkaz:
http://arxiv.org/abs/2305.02866
Autor:
Guo, Jiayan, Du, Lun, Bi, Wendong, Fu, Qiang, Ma, Xiaojun, Chen, Xu, Han, Shi, Zhang, Dongmei, Zhang, Yan
With the rapid development of the World Wide Web (WWW), heterogeneous graphs (HG) have explosive growth. Recently, heterogeneous graph neural network (HGNN) has shown great potential in learning on HG. Current studies of HGNN mainly focus on some HGs
Externí odkaz:
http://arxiv.org/abs/2302.06299
Autor:
CHAI Wenzhao, LIU Jingjing, WANG Xiaoting, MA Xiaojun, TANG Bo, ZHANG Qing, WANG Bin, WANG Xiaomeng, ZHU Shihong, CHEN Wenjin, CHEN Zujun, YANG Quanhui, YANG Rongli, DING Xin, ZHAO Hua, CHENG Wei, DUNA Jun, GAO Jingli, LIU Dawei
Publikováno v:
Xiehe Yixue Zazhi, Vol 15, Iss 3, Pp 522-531 (2024)
Critically ill patients are at high risk for hospital acquired infections, which can significantly increase the mortality rate and treatment costs for these patients. Therefore, in the process of treating the primary disease, strict prevention and co
Externí odkaz:
https://doaj.org/article/a5b76b995042463e87e8904e7971bb91
Researches on analyzing graphs with Graph Neural Networks (GNNs) have been receiving more and more attention because of the great expressive power of graphs. GNNs map the adjacency matrix and node features to node representations by message passing t
Externí odkaz:
http://arxiv.org/abs/2203.10565
Publikováno v:
Proceedings of the ACM Web Conference 2022 (WWW '22), April 25--29, 2022, Virtual Event, Lyon, France
Graph Neural Networks (GNNs) show strong expressive power on graph data mining, by aggregating information from neighbors and using the integrated representation in the downstream tasks. The same aggregation methods and parameters for each node in a
Externí odkaz:
http://arxiv.org/abs/2203.10280
Publikováno v:
In Industrial Crops & Products 15 October 2024 218