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检索条件"机构=Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering"
1190 条 记 录,以下是81-90 订阅
排序:
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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Structure-and Logic-Aware Heterogeneous Graph Learning for Recommendation  40
Structure-and Logic-Aware Heterogeneous Graph Learning for R...
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40th IEEE International Conference on Data engineering, ICDE 2024
作者: Li, Anchen Yang, Bo Huo, Huan Hussain, Farookh Khadeer Xu, Guandong College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China Aalto University Espoo Finland School of Computer Science University of Technology Sydney Sydney Australia Education University of Hong Kong Hong Kong Hong Kong
Recently, there has been a surge in recommendations based on heterogeneous information networks (HINs), attributed to their ability to integrate complex and rich semantics. Despite this advancement, most HIN-based rec... 详细信息
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Meta-GPS++: Enhancing Graph Meta-Learning with Contrastive Learning and Self-Training
arXiv
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arXiv 2024年
作者: Liu, Yonghao Li, Mengyu Li, Ximing Huang, Lan Giunchiglia, Fausto Liang, Yanchun Feng, Xiaoyue Guan, Renchu Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China University of Trento Trento Italy Zhuhai Laboratory of the Key Laboratory of Symbolic Computation and Knowledge Engineering of the Ministry of Education Zhuhai College of Science and Technology Zhuhai China
Node classification is an essential problem in graph learning. However, many models typically obtain unsatisfactory performance when applied to few-shot scenarios. Some studies have attempted to combine meta-learning ... 详细信息
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Joint-Motion Mutual Learning for Pose Estimation in Video  24
Joint-Motion Mutual Learning for Pose Estimation in Video
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32nd ACM International Conference on Multimedia, MM 2024
作者: Wu, Sifan Chen, Haipeng Yin, Yifang Hu, Sihao Feng, Runyang Jiao, Yingying Yang, Ziqi Liu, Zhenguang College of Computer Science and Technology Jilin University Changchun China A STAR Singapore Singapore Georgia Institute of Technology AtlantaGA United States School of Artificial Intelligence Jilin University Changchun China The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China Institute of Blockchain and Data Security Hangzhou China
Human pose estimation in videos has long been a compelling yet challenging task within the realm of computer vision. Nevertheless, this task remains difficult because of the complex video scenes, such as video defocus... 详细信息
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Dilated Convolutional Pixels Affinity Network for Weakly Supervised Semantic Segmentation
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Chinese Journal of Electronics 2021年 第6期30卷 1120-1130页
作者: ZHANG Zhe WANG Bilin YU Zhezhou LI Zhiyuan College of Computer Science and Technology Jilin University Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry
This paper studies semantic segmentation primarily under image-level weak-supervision. Most stateof-the-art technologies have recently used deep classification networks to create small and sparse discriminatory seed r... 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
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Testing Non-Commutativity of Reduce Functions with Multi-Column Inputs
SSRN
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SSRN 2024年
作者: Zhang, Xuan Zhu, Chenlu Li, Ning Zhang, Peng Liu, Lei College of Software Jilin University Jilin China College of Computer Science and Technology Jilin University Jilin China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Jilin China
With the continuous development of the MapReduce programming model, it is necessary to ensure the reliability of MapReduce programs. In practice, the non-commutativity of Reduce functions seriously affects the reliabi... 详细信息
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BA-LORA: BIAS-ALLEVIATING LOW-RANK ADAPTATION TO MITIGATE CATASTROPHIC INHERITANCE IN LARGE LANGUAGE MODELS
arXiv
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arXiv 2024年
作者: Chang, Yupeng Chang, Yi Wu, Yuan School of Artificial Intelligence Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University China International Center of Future Science Jilin University China
Large language models (LLMs) have demonstrated remarkable proficiency across various natural language processing (NLP) tasks. However, adapting LLMs to downstream applications requires computationally intensive and me... 详细信息
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Large Language Model Evaluation via Matrix Nuclear-Norm
arXiv
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arXiv 2024年
作者: Li, Yahan Xia, Tingyu Chang, Yi Wu, Yuan School of Artificial Intelligence Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University China International Center of Future Science Jilin University China
As large language models (LLMs) continue to evolve, efficient evaluation metrics are vital for assessing their ability to compress information and reduce redundancy. While traditional metrics like Matrix Entropy offer... 详细信息
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Learning Semantic Textual Similarity via Topic-informed Discrete Latent Variables
Learning Semantic Textual Similarity via Topic-informed Disc...
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2022 Conference on Empirical Methods in Natural Language Processing, EMNLP 2022
作者: Yu, Erxin Du, Lan Jin, Yuan Wei, Zhepei Chang, Yi School of Artificial Intelligence Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University China International Center of Future Science Jilin University China Faculty of Information Technology Monash University Australia
Recently, discrete latent variable models have received a surge of interest in both Natural Language Processing (NLP) and Computer Vision (CV), attributed to their comparable performance to the continuous counterparts... 详细信息
来源: 评论