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检索条件"机构=The Key Laboratory of Computer Software Engineering"
6018 条 记 录,以下是321-330 订阅
排序:
Deep-Learning-Assisted Complete Targets Coverage in Energy-Harvesting IoT Networks
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IEEE Internet of Things Journal 2025年 第11期12卷 17780-17790页
作者: Wang, Kunsheng Yang, Changlin Chin, Kwan-Wu Xian, Jun Sun Yat-sen University School of Mathematics Guangdong Guangzhou510275 China Sun Yat-sen University School of Software Engineering Zhuhai519082 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia Minnan Normal University School of Mathematics and Statistics Zhangzhou363000 China Sun Yat-sen University Guangdong Provincial Key Laboratory of Computational Science Guangzhou510275 China
Complete targets coverage is required by many Internet of Things (IoT) applications. In this respect, an important goal is to maximize the number of time slots with complete targets coverage. Achieving such coverage i... 详细信息
来源: 评论
Near-Linear Time Approximation Algorithms for k-means with Outliers  41
Near-Linear Time Approximation Algorithms for k-means with O...
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41st International Conference on Machine Learning, ICML 2024
作者: Huang, Junyu Feng, Qilong Huang, Ziyun Xu, Jinhui Wang, Jianxin School of Computer Science and Engineering Central South University Changsha410083 China Xiangjiang Laboratory Changsha410205 China Department of Computer Science and Software Engineering Penn State Erie The Behrend College United States Department of Computer Science and Engineering State University of New York BuffaloNY United States The Hunan Provincial Key Lab of Bioinformatics Central South University Changsha410083 China
The k-means with outliers problem is one of the most extensively studied clustering problems in the field of machine learning, where the goal is to discard up to z outliers and identify a minimum k-means clustering on... 详细信息
来源: 评论
ExcePy: A Python Benchmark for Bugs with Python Built-in Types  29
ExcePy: A Python Benchmark for Bugs with Python Built-in Typ...
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29th IEEE International Conference on software Analysis, Evolution and Reengineering, SANER 2022
作者: Zhang, Xin Yan, Rongjie Yan, Jiwei Cui, Baoquan Yan, Jun Zhang, Jian State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China Technology Center of Software Engineering Institute of Software Chinese Academy of Sciences China University of Chinese Academy of Sciences China
As bugs of Python built-in types can cause code crashes, detecting them is critical to the robustness of the software. Researchers have concluded plenty of patterns for the bug causes and applied these patterns in det... 详细信息
来源: 评论
Linear Time Approximation Algorithm for Column Subset Selection with Local Search  38
Linear Time Approximation Algorithm for Column Subset Select...
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38th Conference on Neural Information Processing Systems, NeurIPS 2024
作者: Zou, Yuanbin Huang, Ziyun Xu, Jinhui Wang, Jianxin Feng, Qilong School of Computer Science and Engineering Central South University Changsha410083 China Xiangjiang Laboratory Changsha410205 China Department of Computer Science and Software Engineering Penn State Erie The Behrend College United States Department of Computer Science and Engineering State University of New York BuffaloNY United States The Hunan Provincial Key Lab of Bioinformatics Central South University Changsha410083 China
The Column Subset Selection (CSS) problem has been widely studied in dimensionality reduction and feature selection. The goal of the CSS problem is to output a submatrix S, consisting of k columns from an n × d i...
来源: 评论
Learning Order Forest for Qualitative-Attribute Data Clustering  27
Learning Order Forest for Qualitative-Attribute Data Cluster...
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27th European Conference on Artificial Intelligence, ECAI 2024
作者: Zhao, Mingjie Feng, Sen Zhang, Yiqun Li, Mengke Lu, Yang Cheung, Yiu-Ming School of Computer Science and Technology Guangdong University of Technology Guangzhou China Shenzhen China School of Computer Science and Software Engineering Shenzhen University Shenzhen China Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University China Department of Computer Science Hong Kong Baptist University Hong Kong
Clustering is a fundamental approach to understanding data patterns, wherein the intuitive Euclidean distance space is commonly adopted. However, this is not the case for implicit cluster distributions reflected by qu... 详细信息
来源: 评论
A Comprehensive Survey on Communication-Efficient Federated Learning in Mobile Edge Environments
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IEEE Communications Surveys and Tutorials 2025年
作者: Jia, Ninghui Qu, Zhihao Ye, Baoliu Wang, Yanyan Hu, Shihong Guo, Song Hohai University Key Laboratory of Water Big Data Technology of Ministry of Water Resources College of Computer Science and Software Engineering Nanjing211100 China Nanjing University State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing210023 China The Hong Kong University of Science and Technology Department of Computer Science and Engineering Kowloon Hong Kong
In traditional centralized machine learning, transmitting raw data to a cloud center incurs high communication costs and raises privacy concerns. This is particularly challenging in mobile edge environments, where dev... 详细信息
来源: 评论
Class-Aware Prompting for Federated Few-Shot Class-Incremental Learning
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IEEE Transactions on Circuits and Systems for Video Technology 2025年
作者: Liang, Fang-Yi Zhan, Yu-Wei Liu, Jiale Zhang, Chong-Yu Chen, Zhen-Duo Luo, Xin Xu, Xin-Shun Shandong University School of Software Jinan250101 China Tsinghua University Department of Computer Science and Technology Beijing100084 China Yunnan Key Laboratory of Software Engineering Kunming650504 China
Few-Shot Class-Incremental Learning (FSCIL) aims to continuously learn new classes from limited samples while preventing catastrophic forgetting. With the increasing distribution of learning data across different clie... 详细信息
来源: 评论
SFPL: Improving CRS via Prompt Learning based Semantic Fusion Module
SFPL: Improving CRS via Prompt Learning based Semantic Fusio...
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Information Technology,Big Data and Artificial Intelligence (ICIBA), International Conference on IEEE International Conference on
作者: Ao Song Zhou Lei Shengbo Chen College of Computer Engineering and Science Shanghai University Shanghai China Shanghai Key Laboratory of Computer Software Testing and Evaluating Shanghai China
With the popularity of the Internet and the massive increase of content production, users are faced with massive information and content, and it is often difficult to accurately and efficiently find the content that m... 详细信息
来源: 评论
CODESWIFT: Accelerating LLM Inference for Efficient Code Generation
arXiv
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arXiv 2025年
作者: Zhao, Qianhui Zhang, Li Liu, Fang Lian, Xiaoli Meng, Qiaoyuanhe Jiao, Ziqian Zhou, Zetong Zhang, Borui Guo, Runlin Li, Jia School of Computer Science and Engineering State Key Laboratory of Complex & Critical Software Environment Beihang University China Key Lab of High Confidence Software Technology Peking University China
Code generation is a latency-sensitive task that demands high timeliness, but the autoregressive decoding mechanism of Large Language Models (LLMs) leads to poor inference efficiency. Existing LLM inference accelerati... 详细信息
来源: 评论
A Neural Architecture Search Method with Multi-Dimensional Correlation Representation for Fault Diagnosis  9
A Neural Architecture Search Method with Multi-Dimensional C...
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9th IEEE Smart World Congress, SWC 2023
作者: Liu, Yumeng Wang, Tingqi Zheng, Xu Tian, Ling Wang, Hongan Institute of Software Chinese Academy of Sciences Beijing Key Laboratory of Human-Computer Interaction Beijing China University of Chinese Academy of Sciences School of Computer Science and Technology Beijing China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu China
As deep learning has become more widely used for fault diagnosis, the shortcomings of model transferability and human model design costs are growing increasingly evident. The current work has tackled each of these two... 详细信息
来源: 评论