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检索条件"机构=Anhui Key Laboratory of Software in Computing and Communication"
453 条 记 录,以下是141-150 订阅
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Cooperative communications in 5G point-to-multipoint systems for Smart Grid communications  7
Cooperative communications in 5G point-to-multipoint systems...
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7th International Conference on Information Science and Control Engineering, ICISCE 2020
作者: Yu, Hao Jin, Xin Li, Zhenwei Dong, Yawen Yang, Yang Liu, Zhengyuan Yin, Menjun State Grid Anhui Power Co. LTD. Information and Communication Branch State Grid Information Telecommunication Group Anhui Jiyuan Software Co. Ltd China Beijing University of Posts and Telecommunications The State Key Laboratory of Networking and Switching Technology China
With the development of wireless communication network, 5G H-CRAN network has gradually become the focus of research. The increasing demands for mobile data multimedia services and high bandwidth multimedia services r... 详细信息
来源: 评论
Hierarchical Reverse Games for the Resource Ecosystem in Cloud-Edge computing
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IEEE Transactions on Consumer Electronics 2024年
作者: Pei, Manlin Wang, Chenyu Wang, Xia Zheng, Zhigao Huang, Jianhui Wang, Shengling Guo, Yufei School of Computer and Information Technology Beijing Jiaotong University Beijing China Department of Computer Science Georgia State University United States Beijing University of Technology School of Statistics and Data Science Faculty of Science Beijing China Institute of Artificial Intelligence School of Computer Science National Engineering Research Center for Multimedia Software Hubei Key Laboratory of Multimedia and Network Communication Engineering Hubei Luojia Laboratory Wuhan University Wuhan China Chinese Academy of Sciences Institute of Computing Technology Beijing China Beijing Normal University School of Artificial Intelligence Beijing China George Washington University Department of Statistics United States
Edge computing has emerged as a killer technology for a hyper-connected world due to its distributed architecture and customer-proximity property. Combined edge nodes with the cloud data center, a cloud-edge computing... 详细信息
来源: 评论
DarkFed: A Data-Free Backdoor Attack in Federated Learning
arXiv
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arXiv 2024年
作者: Li, Minghui Wan, Wei Ning, Yuxuan Hu, Shengshan Xue, Lulu Zhang, Leo Yu Wang, Yichen School of Software Engineering Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia
Federated learning (FL) has been demonstrated to be susceptible to backdoor attacks. However, existing academic studies on FL backdoor attacks rely on a high proportion of real clients with main task-related data, whi... 详细信息
来源: 评论
Why Does Little Robustness Help? A Further Step Towards Understanding Adversarial Transferability
arXiv
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arXiv 2023年
作者: Zhang, Yechao Hu, Shengshan Zhang, Leo Yu Shi, Junyu Li, Minghui Liu, Xiaogeng Wan, Wei Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia School of Computer Science and Technology Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab
Adversarial examples for deep neural networks (DNNs) have been shown to be transferable: examples that successfully fool one white-box surrogate model can also deceive other black-box models with different architectur... 详细信息
来源: 评论
MLFuse: Multi-Scenario Feature Joint Learning for Multi-Modality Image Fusion
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IEEE Transactions on Multimedia 2025年
作者: Lei, Jia Li, Jiawei Liu, Jinyuan Wang, Bin Zhou, Shihua Zhang, Qiang Wei, Xiaopeng Kasabov, Nikola K. Dalian University Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian116622 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China Dalian University of Technology School of Mechanical Engineering Dalian116024 China Dalian University of Technology School of Computer Science and Technology Dalian116024 China Auckland University of Technology Knowledge Engineering and Discovery Research Institute Auckland1010 New Zealand Ulster University Intelligent Systems Research Center LondonderryBT52 1SA United Kingdom
Multi-modality image fusion (MMIF) entails synthesizing images with detailed textures and prominent objects. Existing methods tend to use general feature extraction to handle different fusion tasks. However, these met... 详细信息
来源: 评论
A Four-Pronged Defense Against Byzantine Attacks in Federated Learning
arXiv
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arXiv 2023年
作者: Wan, Wei Hu, Shengshan Li, Minghui Lu, Jianrong Zhang, Longling Zhang, Leo Yu Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia School of Computer Science and Technology Huazhong University of Science and Technology China National Engineering Research Center for Big Data Technology and System Services Computing Technology and System Lab Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab
Federated learning (FL) is a nascent distributed learning paradigm to train a shared global model without violating users' privacy. FL has been shown to be vulnerable to various Byzantine attacks, where malicious ... 详细信息
来源: 评论
Accepted Influence Maximization under Linear Threshold Model on Large-Scale Social Networks
Accepted Influence Maximization under Linear Threshold Model...
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IEEE International Conference on Trust, Security and Privacy in computing and communications (TrustCom)
作者: Xiaojuan Yang Jiaxing Shang Linjiang Zheng Dajiang Liu Shu Fu Baohua Qiang Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education College of Computer Science Chongqing University Chongqing China School of Microelectronics and Communication Engineering Chongqing University Chongqing China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic Technology Guilin China
The influence maximization (IM) problem, which aims to find $k$ most influential individuals from a social network to maximize the influence spread, has been extensively studied. Existing works all rely on the assum... 详细信息
来源: 评论
The g-dominance Relation for Preference-Based Evolutionary Multi-Objective Optimization
The g-dominance Relation for Preference-Based Evolutionary M...
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2019 IEEE Congress on Evolutionary Computation, CEC 2019
作者: Luo, Wenjian Shi, Luming Lin, Xin Coello Coello, Carlos A. Anhui Province Key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei230027 China Departmento de Sistemas UAM-Azcapotzalco Mexico City Mexico
In evolutionary multi-objective optimization, the results generated by an evolutionary algorithm usually contain an approximation, as good as possible, of the entire Pareto-optimal front. However, sometimes the number... 详细信息
来源: 评论
MISA: UNVEILING THE VULNERABILITIES IN SPLIT FEDERATED LEARNING
arXiv
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arXiv 2023年
作者: Wan, Wei Ning, Yuxuan Hu, Shengshan Xue, Lulu Li, Minghui Zhang, Leo Yu Jin, Hai School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of Software Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Hubei Key Laboratory of Distributed System Security China Hubei Engineering Research Center on Big Data Security China Cluster and Grid Computing Lab China
Federated learning (FL) and split learning (SL) are prevailing distributed paradigms in recent years. They both enable shared global model training while keeping data localized on users' devices. The former excels...
来源: 评论
A Quantum Probability Driven Framework for Joint Multi-Modal Sarcasm, Sentiment and Emotion Analysis
arXiv
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arXiv 2023年
作者: Liu, Yaochen Zhang, Yazhou Song, Dawei School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China School of Computing and Communications The Open University Walton Hall United Kingdom School of Nursing The Hong Kong Polytechnic University Hong Kong Ministry of Education China Artificial Intelligence Laboratory China Mobile Communication Group Tianjin Co. Ltd. China State Key Lab. for Novel Software Technology Nanjing University Nanjing China Zhengzhou University of Light Industry China
Sarcasm, sentiment, and emotion are three typical kinds of spontaneous affective responses of humans to external events and they are tightly intertwined with each other. Such events may be expressed in multiple modali... 详细信息
来源: 评论