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检索条件"机构=Key Laboratory of Symbolic Computing and Knowledge Engineering"
1005 条 记 录,以下是231-240 订阅
排序:
DeepSelective: Feature Gating and Representation Matching for Interpretable Clinical Prediction
arXiv
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arXiv 2025年
作者: Zhang, Ruochi Yang, Qian Wang, Xiaoyang Wu, Haoran Zhou, Qiong Wang, Yu Li, Kewei Wang, Yueying Fan, Yusi Zhang, Jiale Huang, Lan Liu, Chang Zhou, Fengfeng College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Beijing Life Science Academy Beijing102209 China Syneron Technology Guangzhou510700 China
The rapid accumulation of Electronic Health Records (EHRs) has transformed healthcare by providing valuable data that enhance clinical predictions and diagnoses. While conventional machine learning models have proven ... 详细信息
来源: 评论
Dynamic QoS-Driven Framework for Co-Scheduling of Distributed Long-Running Applications on Shared Clusters
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IEEE Transactions on Cloud computing 2025年
作者: Zhu, Jianyong Wang, Hongtao Su, Pan Wang, Yang Pan, Weihua North China Electric Power University Department of Computer China Hebei Key Laboratory of Knowledge Computing for Energy & Power China Ministry of Education Engineering Research Center of Intelligent Computing for Complex Energy Systems China
Cloud service providers typically co-locate various workloads within the same production cluster to improve resource utilization and reduce operational costs. These workloads primarily consist of batch analysis jobs c... 详细信息
来源: 评论
TYPE-SUPERVISED SEQUENCE LABELING BASED ON THE HETEROGENEOUS STAR GRAPH FOR NAMED ENTITY RECOGNITION
arXiv
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arXiv 2022年
作者: Wen, Xueru Zhou, Changjiang Tang, Haotian Liang, Luguang Jiang, Yu Qi, Hong College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University China
Named entity recognition is a fundamental task in natural language processing, identifying the span and category of entities in unstructured texts. The traditional sequence labeling methodology ignores the nested enti... 详细信息
来源: 评论
END-TO-END ENTITY DETECTION WITH PROPOSER AND REGRESSOR
arXiv
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arXiv 2022年
作者: Wen, Xueru Zhou, Changjiang Tang, Haotian Liang, Luguang Jiang, Yu Qi, Hong College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University China
Named entity recognition is a traditional task in natural language processing. In particular, nested entity recognition receives extensive attention for the widespread existence of the nesting scenario. The latest res... 详细信息
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ON A NOVEL UCP RESULT AND ITS APPLICATION TO INVERSE CONDUCTIVE SCATTERING
arXiv
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arXiv 2024年
作者: Diao, Huaian Fei, Xiaoxu Liu, Hongyu School of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China School of Mathematics and Statistics Central South University Changsha410083 China Department of Mathematics City University of Hong Kong Kowloon Hong Kong
In this paper, we derive a novel Unique Continuation Principle (UCP) for a system of second-order elliptic PDEs and apply it to investigate inverse problems in conductive scattering. The UCP relaxes the typical assump... 详细信息
来源: 评论
DK-STN: A Domain knowledge Embedded Spatio-Temporal Network Model for MJO Forecast
SSRN
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SSRN 2023年
作者: Li, Hongliang Zhang, Nong Xu, Zhewen Li, Xiang Liu, Changzheng Zhao, Chongbo Wu, Jie College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun130012 China China Meteorological Administration Key Laboratory for Climate Prediction Studies National Climate Center Beijing100081 China
Understanding and predicting the Madden-Julian Oscillation (MJO) is fundamental for precipitation forecasting and disaster prevention. To date, long-term and accurate MJO prediction has remained a challenge for resear... 详细信息
来源: 评论
Causality-inspired Unsupervised Domain Adaptation with Target Style Imitation for Medical Image Segmentation
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IEEE Transactions on Circuits and Systems for Video Technology 2025年
作者: Song, Jincai Chen, Haipeng Lyu, Yingda Nie, Weizhi Liu, An-An Jilin University College of Computer Science and Technology Jilin Changchun130012 China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin Changchun130012 China Jilin University Public Computer Education and Research Center Jilin Changchun130012 China Tianjin University School of Electrical and Information Engineering Tianjin300072 China
Deep learning performance may decrease substantially with unseen heterogeneous data. While most unsupervised domain adaptation (UDA) methods seek to address this through image alignment, they often ignore uncertainty ... 详细信息
来源: 评论
Unknown Task Selection and Worker Recruitment Using Two-Stage Multi-Armed Bandit in Crowdsensing
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IEEE Internet of Things Journal 2025年
作者: Song, Haoyuan Li, Peng Du, Rui Yu, Hai Huang, Weiyi Nie, Lei Bao, Haizhou Liu, Qin Wuhan University of Science and Technology School of Computer Science and Technology Wuhan430065 China Wuhan University of Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan430065 China Hubei Polytechnic University School of Computer Huangshi435003 China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun130012 China Wuhan University School of Cyber Science and Engineering Wuhan430072 China
Mobile Crowdsensing (MCS) faces significant challenges in selecting tasks with expected high revenue and recruiting workers with expected high qualities to maximize overall utility. Existing approaches often assume th... 详细信息
来源: 评论
Task Delay and Energy Consumption Minimization for Low-altitude MEC via Evolutionary Multi-objective Deep Reinforcement Learning
arXiv
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arXiv 2025年
作者: Sun, Geng Ma, Weilong Li, Jiahui Sun, Zemin Wang, Jiacheng Niyato, Dusit Mao, Shiwen College of Computer Science and Technology Jilin University Changchun130012 China 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 Singapore639798 Singapore College of Software Jilin University Changchun130012 China Department of Electrical and Computer Engineering Auburn University AuburnAL36849-5201 United States
The low-altitude economy (LAE), driven by unmanned aerial vehicles (UAVs) and other aircraft, has revolutionized fields such as transportation, agriculture, and environmental monitoring. In the upcoming six-generation... 详细信息
来源: 评论
Elucidating Spatial Complex Structures from Mass Spectrometry Imaging with Deep Multimodal Model  1
Elucidating Spatial Complex Structures from Mass Spectrometr...
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1st IEEE International Conference on Medical Artificial Intelligence, MedAI 2023
作者: Cui, Jiangnan Xia, Junjie Li, Xuan Wang, Yan Qiu, Fufang Xu, Yaochen Xu, Keren Zuo, Chunman School of Computer Science and Technology Institute of Artificial Intelligence Donghua University Shanghai China College of Computer Science and Technology Jilin University Changchun China Huashan Hospital Department of Neurosurgery Shanghai China Shanghai Institute of Biochemistry and Cell Biology Center for Excellence in Molecular Cell Science Chinese Academy of Sciences Cas Key Laboratory of Systems Biology Shanghai China Institute of Artificial Intelligence Donghua University Shanghai China Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun China
Spatial mass spectrometry imaging (SMSI) technology has enabled the characterization of biomolecule patterns within the tissue microenvironment, yet its analyses suffer from substantial noise. The lack of effective me... 详细信息
来源: 评论