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检索条件"机构=Key Laboratory of Data Engineering and Visual Computing"
1544 条 记 录,以下是491-500 订阅
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Exploring Patent Transformation Event: Forecasting Patent Transfer Time
Exploring Patent Transformation Event: Forecasting Patent Tr...
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International Conference on Computer Supported Cooperative Work in Design
作者: Jinchen Huo Weidong Liu Yang Li Yan Cao College of Computer Science Inner Mongolia University China Institute of Scientific and Technical Information of China China National & Local Joint Engineering Research Center of Intelligent Information Processing Technology for Mongolian China Inner Mongolia Key Laboratory of Social Computing and Data Processing China Inner Mongolia Engineering Laboratory for Big Data Analysis Technology China
As the largest source of technical information around the world, patents are regarded as an essential crystallization and carrier of knowledge and technological innovation. Patent transformation is conducive not only ...
来源: 评论
Rethinking Super-Resolution as Text-Guided Details Generation
arXiv
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arXiv 2022年
作者: Ma, Chenxi Yan, Bo Lin, Qing Tan, Weimin Chen, Siming School of Computer Science Shanghai Key Laboratory of Intelligent Information Processing Shanghai Collaborative Innovation Center of Intelligent Visual Computing Fudan University China School of Data Science Fudan University China
Deep neural networks have greatly promoted the performance of single image super-resolution (SISR). Conventional methods still resort to restoring the single high-resolution (HR) solution only based on the input of im... 详细信息
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Enhancing Security and Privacy in Federated Learning using Low-Dimensional Update Representation and Proximity-Based Defense
arXiv
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arXiv 2024年
作者: Li, Wenjie Fan, Kai Zhang, Jingyuan Li, Hui Lim, Wei Yang Bryan Yang, Qiang The State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China The College of Computing and Data Science Nanyang Technological University 639798 Singapore The Department of Computer Science and Engineering Hong Kong University of Science and Technology 999077 Hong Kong
Federated Learning (FL) is a promising privacy-preserving machine learning paradigm that allows data owners to collaboratively train models while keeping their data localized. Despite its potential, FL faces challenge... 详细信息
来源: 评论
A3-CodGen: A Repository-Level Code Generation Framework for Code Reuse with Local-Aware, Global-Aware, and Third-Party-Library-Aware
arXiv
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arXiv 2023年
作者: Liao, Dianshu Pan, Shidong Sun, Xiaoyu Ren, Xiaoxue Huang, Qing Xing, Zhenchang Jin, Huan Li, Qinying School of Computing Australian National University Australia School of Computer Information Engineering Jiangxi Normal University China CSIRO’s Data61 Australia State Key Laboratory of Blockchain and Data Security Zhejiang University China Institute of Blockchain and Data Security China Jiangxi University of Technology China
LLM-based code generation tools are essential to help developers in the software development process. Existing tools often disconnect with the working context, i.e., the code repository, causing the generated code to ... 详细信息
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Deep Kernel Embedded Clustering Network
SSRN
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SSRN 2024年
作者: Ren, Lina Huang, Ruizhang Chen, Yanping Lin, Chuan Qin, Yongbin State Key Laboratory of Public Big Data Text Computing and Cognitive Intelligence Engineering Research Center of National Education Ministry College of Computer Science and Technology Guizhou University Guiyang550025 China Department of Information Engineering Guizhou Light Industry Technical College Guiyang550025 China
In this paper, we propose a deep kernel embedded clustering network, namely DKEC, which learns data partitions with kernelized semantic embeddings of data samples via a self-supervised deep neural network. A kernelize... 详细信息
来源: 评论
Burst-Sensitive Traffic Forecast Via Multi-Property Personalized Fusion in Federated Learning
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IEEE Transactions on Mobile computing 2025年
作者: Xue, Jingjing Sun, Sheng Liu, Min Wang, Yuwei Meng, Xuying Wang, Jingyuan Zhang, JunBo Xu, Ke Chinese Academy of Sciences University of Chinese Academy of Sciences Institute of Computing Technology Beijing China Chinese Academy of Sciences Institute of Computing Technology Beijing China Beihang University School of Computer Science and Engineering China Beihang University MIIT Key Laboratory of Data Intelligence and Management Beijing China JD Technology JD iCity China JD Intelligent Cities Research China Tsinghua University Department of Computer Science and Technology Beijing China Zhongguancun Laboratory Beijing China
For distributed network traffic prediction with data localization and privacy protection, Federated Learning (FL) enables collaborative training without raw data exchange across Base Stations (BSs). Nevertheless, traf... 详细信息
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Unifying and Improving Graph Convolutional Neural Networks with Wavelet Denoising Filters  23
Unifying and Improving Graph Convolutional Neural Networks w...
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2023 World Wide Web Conference, WWW 2023
作者: Wan, Liangtian Li, Xiaona Han, Huijin Yan, Xiaoran Sun, Lu Ning, Zhaolong Xia, Feng Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province School of Software Dalian University of Technology Dalian China Research Center of Big Data Intelligence Research Institute of Artificial Intelligence Zhejiang Lab Hangzhou China Department of Communication Engineering Institute of Information Science Technology Dalian Maritime University Dalian China School of Communication and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China School of Computing Technologies Rmit University Melbourne Australia
Graph convolutional neural network (GCN) is a powerful deep learning framework for network data. However, variants of graph neural architectures can lead to drastically different performance on different tasks. Model ... 详细信息
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CIMI4D: A Large Multimodal Climbing Motion dataset under Human-scene Interactions
arXiv
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arXiv 2023年
作者: Yan, Ming Wang, Xin Dai, Yudi Shen, Siqi Wen, Chenglu Xu, Lan Ma, Yuexin Wang, Cheng Fujian Key Laboratory of Sensing and Computing for Smart Cities Xiamen University China National Institute for Data Science in Health and Medicine Xiamen University China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China School of Informatics Xiamen University China Shanghai Engineering Research Center of Intelligent Vision and Imaging ShanghaiTech University China
Motion capture is a long-standing research problem. Although it has been studied for decades, the majority of research focus on ground-based movements such as walking, sitting, dancing, etc. Off-grounded actions such ... 详细信息
来源: 评论
A Fusion Tuning Method for Named Entity Recognition  12th
A Fusion Tuning Method for Named Entity Recognition
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12th CCF Conference on Bigdata, Bigdata 2024
作者: Wang, Jitian Chen, Yanping Zou, Anqi Qin, Yongbin Huang, Ruizhang Text Computing and Cognitive Intelligence Engineering Research Center of National Education Ministry Guizhou University Guiyang550025 China State Key Laboratory of Public Big Data Guizhou University Guiyang China College of Computer Science and Technology Guizhou University Guiyang550025 China
In named entity recognition, the main methods for constructing deep neural networks are fine-tuning and prompt tuning. Fine-tuning is a commonly used paradigm to optimize neural networks by using task-specific objecti... 详细信息
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NOBGP: A Novel Optimized Balanced Graph Partitioning Algorithm  19th
NOBGP: A Novel Optimized Balanced Graph Partitioning Algorit...
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19th CCF Conference on Computer Supported Cooperative Work and Social computing, ChineseCSCW 2024
作者: Chen, Jiebin Hu, Ziqiang Ye, Renjie Zhang, Qishan Guo, Kun College of Computer and Data Science Fuzhou University Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou350108 China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350108 China Xianda College of Economics and Humanities Shanghai International Studies University Shanghai China
Large-scale graphs have become prevalent with the advent of the big data era. Distributed graph computing systems are commonly used for processing and analyzing large-scale graphs, with graph partitioning being a key ... 详细信息
来源: 评论