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检索条件"机构=Key Laboratory of Symbolic Computation and Knowledge Engineering for Ministry of Education"
1105 条 记 录,以下是21-30 订阅
排序:
Efficient Sharing of Energy Consumption Data: A Privacy-Preserving Threshold Aggregation Approach
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IEEE Internet of Things Journal 2025年
作者: Li, Guohao Zhou, Lu Lian, Jiale Liu, Siyi Yang, Li Zhong, Yantao Li, Qiang Xidian University School of Computer Science and Technology Xi’an China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun China Co. Ltd Guangdong Shenzhen China
Energy consumption data collected by smart meters is increasingly used by various subscribers in the smart grid for load management, energy monitoring, and policy planning. To protect user privacy, edge-assisted priva... 详细信息
来源: 评论
KSSANet: KAN-Driven Spatial-Spectral Attention Networks for Hyperspectral Image Super-Resolution
KSSANet: KAN-Driven Spatial-Spectral Attention Networks for ...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Baisong Li Xingwang Wang Haixiao Xu College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Krowledge Engineering of Ministry of Education Jilin University
Due to the limitations of physical imaging, acquiring high-resolution hyperspectral images (HR-HSIs) has always been a significant challenge. Single hyperspectral image super-resolution (SHSR) technology aims to gener... 详细信息
来源: 评论
SSRMamba: Efficient Visual State Space Model for Spectral Super-Resolution
SSRMamba: Efficient Visual State Space Model for Spectral Su...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Baisong Li Xingwang Wang Haixiao Xu College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Krowledge Engineering of Ministry of Education Jilin University
Spectral super-resolution, which reconstructs hyperspectral images (HSI) from a single RGB image, has garnered increasing attention. Due to the limitations of CNN structures in spectral modeling and the high computati... 详细信息
来源: 评论
Boosting Weak-to-Strong Agents in Multiagent Reinforcement Learning via Balanced PPO
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IEEE Transactions on Neural Networks and Learning Systems 2025年 第5期36卷 9136-9149页
作者: Huang, Sili Chen, Hechang Piao, Haiyin Sun, Zhixiao Chang, Yi Sun, Lichao Yang, Bo Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education School of Artificial Intelligence Changchun130012 China Jilin University School of Artificial Intelligence Changchun130012 China Northwestern Polytechnical University Unmanned System Research Institute Xi’an710068 China Lehigh University Department of Computer Science and Engineering BethlehemPA18015 United States Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineer of Ministry of Education School of Computer Science and Technology Changchun130012 China
Multiagent policy gradients (MAPGs), an essential branch of reinforcement learning (RL), have made great progress in both industry and academia. However, existing models do not pay attention to the inadequate training... 详细信息
来源: 评论
A Correlated Data-Driven Collaborative Beamforming Approach for Energy-efficient IoT Data Transmission
arXiv
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arXiv 2025年
作者: Li, Yangning Kang, Hui Li, Jiahui Sun, Geng Sun, Zemin Wang, Jiacheng Zhao, Changyuan Niyato, Dusit College of Computer Science and Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Computing and Data Science Nanyang Technological University 639798 Singapore College of Computing and Data Science Nanyang Technological University Singapore
An expansion of Internet of Things (IoTs) has led to significant challenges in wireless data harvesting, dissemination, and energy management due to the massive volumes of data generated by IoT devices. These challeng... 详细信息
来源: 评论
Enhancing Unsupervised Graph Few-shot Learning via Set Functions and Optimal Transport  25
Enhancing Unsupervised Graph Few-shot Learning via Set Funct...
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Proceedings of the 31st ACM SIGKDD Conference on knowledge Discovery and Data Mining V.1
作者: Yonghao Liu Fausto Giunchiglia Ximing Li Lan Huang Xiaoyue Feng Renchu Guan Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China Department of Information Engineering and Computer Science University of Trento Trento Italy
Graph few-shot learning has garnered significant attention for its ability to rapidly adapt to downstream tasks with limited labeled data, sparking considerable interest among researchers. Recent advancements in graph... 详细信息
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VECLLF: A vehicle-edge collaborative lifelong learning framework for anomaly detection in VANETs
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Computer Networks 2025年 265卷
作者: Wang, Yingqing Liang, Yanhua Huang, Yue Qin, Guihe Jilin University College of Computer Science and Technology Changchun130012 China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China Jilin University Center for Computer Fundamental Education Changchun130012 China
With the rapid development of intelligent connected vehicles, Vehicular Ad Hoc Network (VANET) is widely used in intelligent transportation systems. VANETs are vulnerable to attacks in their operating environments, su... 详细信息
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AHMSA-Net: Adaptive Hierarchical Multi-Scale Attention Network for Micro-Expression Recognition
arXiv
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arXiv 2025年
作者: Zhang, Lijun Zhang, Yifan Tang, Weicheng Sun, Xinzhi Wang, Xiaomeng Li, Zhanshan College of Computer Science and Technology Jilin University Changchun Jilin130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun Jilin130012 China
Micro-expression recognition (MER) presents a significant challenge due to the transient and subtle nature of the motion changes involved. In recent years, deep learning methods based on attention mechanisms have made... 详细信息
来源: 评论
Stochastic Block Models for Complex Network Analysis: A Survey
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ACM Transactions on knowledge Discovery from Data 2025年 第3期19卷 1-35页
作者: Liu, Xueyan Song, Wenzhuo Musial, Katarzyna Li, Yang Zhao, Xuehua Yang, Bo College of Computer Science and Technology Jilin University Changchun China School of Information Science and Technology Northeast Normal University Changchun China Complex Adaptive Systems Lab Data Science Institute University of Technology Sydney Sydney Australia Aviation University of the Air Force Changchun China School of Digital Media Shenzhen Institute of Information Technology Shenzhen China Key Laboratory of Symbolic Computation and Knowledge Engineer Jilin University Ministry of Education Changchun China
Complex networks enable to represent and characterize the interactions between entities in various complex systems which widely exist in the real world and usually generate vast amounts of data about all the elements,... 详细信息
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Fairness-Aware Budgeted Edge Server Placement for Connected Autonomous Vehicles
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IEEE Transactions on Mobile Computing 2025年 第6期24卷 4762-4776页
作者: Wu, Jintao Xu, Xiaolong Cui, Guangming Zhang, Yiwen Qi, Lianyong Dou, Wanchun Cai, Zhipeng Nanjing University of Information Science & Technology Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of Software Nanjing210044 China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China Nanjing University of Information Science & Technology Jiangsu Province Engineering Research Center of Advanced Computing and Intelligent Services School of Software China Nanjing University State Key Laboratory for Novel Software Technology China Anhui University School of Computer Science and Technology Anhui230031 China College of Computer Science and Technology Qingdao266580 China Nanjing University State Key Laboratory for Novel Software Technology Nanjing210023 China Georgia State University Department of Computer Science United States
Mobile edge computing (MEC) considerably enhances the capabilities and performance of connected autonomous vehicles (CAVs) by deploying edge servers (ESs) on roadside units (RSUs) near CAVs, thereby ensuring low-laten... 详细信息
来源: 评论