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检索条件"机构=A Key Laboratory of Symbolic Computation and Knowledge Engineering"
1216 条 记 录,以下是221-230 订阅
排序:
Why Misinformation is Created? Detecting them by Integrating Intent Features
arXiv
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arXiv 2024年
作者: Wang, Bing Fu, Bo Li, Ximing Pei, Songwen Li, Changchun Wang, Shengsheng College of Computer Science and Technology Jilin University Changchun Jilin China Liaoning Normal University Liaoning Dalian China University of Shanghai for Science and Technology Shanghai China Key Laboratory of Symbolic Computation and Knowledge Engineering The Ministry of Education Jilin University China
Various social media platforms, e.g., Twitter and Reddit, allow people to disseminate a plethora of information more efficiently and conveniently. However, they are inevitably full of misinformation, causing damage to... 详细信息
来源: 评论
Formal Reachability Analysis for Multi-Agent Reinforcement Learning Systems
Formal Reachability Analysis for Multi-Agent Reinforcement L...
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作者: Wang, Xiaoyan Peng, Jun Li, Shuqiu Li, Bing College of Computer Science and Technology Jilin University Changchun130012 China Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun130012 China
Reachability analysis is one of the most basic and challenging problems in verification. We investigate this problem in multi-agent reinforcement learning (MARL) system by transforming the reachability analysis to dec... 详细信息
来源: 评论
Discrepancy-Guided Reconstruction Learning for Image Forgery Detection
arXiv
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arXiv 2023年
作者: Shi, Zenan Chen, Haipeng Chen, Long Zhang, Dong College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University China Department of CSE The Hong Kong University of Science and Technology Hong Kong
In this paper, we propose a novel image forgery detection paradigm for boosting the model learning capacity on both forgery-sensitive and genuine compact visual patterns. Compared to the existing methods that only foc... 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
来源: 评论
Multi-Task Self-Supervised Learning for Medical Image Segmentation
Multi-Task Self-Supervised Learning for Medical Image Segmen...
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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
作者: Bo Wang Hang Zhao Xiongfei Li Mingjie Tian Bo Huang Feiyang Yang Intelligent Information Processing Laboratory Yanbian University Yanji China College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China School of Artificial Intelligence Jilin University Changchun China
Although medical image segmentation has achieved remarkable results with supervised learning, obtaining labeled data remains challenging and costly. To counteract this, we present the MTSPSeg, a multi-task self-superv...
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
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
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
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Efficient Heuristics for Learning Scalable Bayesian Network Classifier from Labeled and Unlabeled Data
SSRN
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SSRN 2023年
作者: Wang, Limin Wang, Junjie Guo, Lu Li, Qilong Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China College of Software Jilin University Changchun130012 China College of Instrumentation and Electrical Engineering Jilin University Changchun130012 China
Naive Bayes (NB) is one of the top ten machine learning algorithms whereas its attribute independence assumption rarely holds in practice. A feasible and efficient approach to improving NB is relaxing the assumption b... 详细信息
来源: 评论
PLPR: Towards Efficient and Privacy-Preserving LBSNs-Based POI Recommendation in Cloud
PLPR: Towards Efficient and Privacy-Preserving LBSNs-Based P...
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IEEE International Conference on Communications (ICC)
作者: Lili Sun Yonggang Zhang Yandong Zheng Rongxing Lu Hui Zhu Key Laboratory of Symbolic Computation and Knowledge Engineer Jilin University Changchun China State Key Laboratory of Integrated Services Networks Xidian University Xi'an China Facuity of Computer Science University of New Brunswick Fredericton Canada
With the popularity of location-based social networks (LBSNs), locations and social relationships have been considered to be important factors in point-of-interest (POI) recommendation services. The boom of cloud comp...
来源: 评论