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检索条件"机构=Academy of Computer Science and Software Engineering"
1508 条 记 录,以下是1351-1360 订阅
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A user model based on mobile environment
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Ruan Jian Xue Bao/Journal of software 2011年 第SUPPL. 2期22卷 120-128页
作者: Du, Yi Tian, Feng Dai, Guo-Zhong Wang, Feng Wang, Hong-An Intelligence Engineering Laboratory Institute of Software Chinese Academy of Sciences Beijing 100190 China School of Information Science and Engineering Graduate University Chinese Academy of Sciences Beijing 100190 China Yunnan Provincial Key Laboratory of Computer Application Kunming University of Science and Technology Kunming 650500 China
It's very important to help developers design user interface for application in an intelligent user interface. Nowadays, the number of mobile based applications increases greatly, but there are no proper user mode... 详细信息
来源: 评论
DPA-2:a large atomic model as a multitask learner
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npj Computational Materials 2024年 第1期10卷 185-199页
作者: Duo Zhang Xinzijian Liu Xiangyu Zhang Chengqian Zhang Chun Cai Hangrui Bi Yiming Du Xuejian Qin Anyang Peng Jiameng Huang Bowen Li Yifan Shan Jinzhe Zeng Yuzhi Zhang Siyuan Liu Yifan Li Junhan Chang Xinyan Wang Shuo Zhou Jianchuan Liu Xiaoshan Luo Zhenyu Wang Wanrun Jiang Jing Wu Yudi Yang Jiyuan Yang Manyi Yang Fu-Qiang Gong Linshuang Zhang Mengchao Shi Fu-Zhi Dai Darrin M.York Shi Liu Tong Zhu Zhicheng Zhong Jian Lv Jun Cheng Weile Jia Mohan Chen Guolin Ke Weinan E Linfeng Zhang Han Wang AI for Science Institute BeijingP.R.China DP Technology BeijingP.R.China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingP.R.China State Key Lab of Processors Institute of Computing TechnologyChinese Academy of SciencesBeijingP.R.China University of Chinese Academy of Sciences BeijingP.R.China HEDPS CAPTCollege of EngineeringPeking UniversityBeijingP.R.China Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboP.R.China CAS Key Laboratory of Magnetic Materials and Devices and Zhejiang Province Key Laboratory of Magnetic Materials and Application Technology Chinese Academy of SciencesNingboP.R.China School of Electronics Engineering and Computer Science Peking UniversityBeijingP.R.China Shanghai Engineering Research Center of Molecular Therapeutics&New Drug Development School of Chemistry and Molecular EngineeringEast China Normal UniversityShanghaiP.R.China Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine and Department of Chemistry and Chemical BiologyRutgers UniversityPiscatawayNJUSA Department of Chemistry Princeton UniversityPrincetonNJUSA College of Chemistry and Molecular Engineering Peking UniversityBeijingP.R.China Yuanpei College Peking UniversityBeijingP.R.China School of Electrical Engineering and Electronic Information Xihua UniversityChengduP.R.China State Key Laboratory of Superhard Materials College of PhysicsJilin UniversityChangchunP.R.China Key Laboratory of Material Simulation Methods&Software of Ministry of Education College of PhysicsJilin UniversityChangchunP.R.China International Center of Future Science Jilin UniversityChangchunP.R.China Key Laboratory for Quantum Materialsof Zhejiang Province Department of PhysicsSchool of ScienceWestlake UniversityHangzhouP.R.China Atomistic Simulations Italian Institute of TechnologyGenovaItaly State Key Laboratory of Physical Chemistry of Solid Surface iChEMCollege of Chemistry and Chemical EngineeringXiame
The rapid advancements in artificial intelligence(AI)are catalyzing transformative changes in atomic modeling,simulation,and ***-driven potential energy models havedemonstrated the capability to conduct large-scale,lo... 详细信息
来源: 评论
Self-Ensembling GAN for Cross-Domain Semantic Segmentation
arXiv
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arXiv 2021年
作者: Xu, Yonghao He, Fengxiang Du, Bo Tao, Dacheng Zhang, Liangpei The State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan430079 China Vienna1030 Austria JD Explore Academy *** Inc. Beijing100176 China School of Computer Science National Engineering Research Center for Multimedia Software Institute of Artificial Intelligence Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan430079 China
Deep neural networks (DNNs) have greatly contributed to the performance gains in semantic segmentation. Nevertheless, training DNNs generally requires large amounts of pixel-level labeled data, which is expensive and ... 详细信息
来源: 评论
The spirit of evolutionary algorithms
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Journal of Computing and Information Technology 1999年 第1期7卷 1-18页
作者: Michalewicz, Zbigniew Esquivel, Susana Gallarti, Raul Michalewicz, Maciej Tao, Guo Trojanowski, Krzysztof Department of Computer Science University of North Carolina CharlotteNC28223 United States Departamento de Informatica Facuitad de Cs. Fisico-Matematicas y Naturales Universidad Naclonal de San Luis Ejercito de los Andes 950 local 106 San Luis5700 Argentina Institute of Computer Science Polish Academy of Sciences ul. Ordona 21 Warsaw01-237 Poland State Key Laboratory of Software Engineering Wuhan University WuhanHubei430072 China
Evolutionary algorithms (EAs), which are based on a powerful principle of evolution: survival of the fittest, and which model some natural phenomena: genetic inheritance and Darwinian strife for survival, constitute a... 详细信息
来源: 评论
Finite Volume Graph Network(FVGN): Predicting unsteady incompressible fluid dynamics with finite volume informed neural network
arXiv
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arXiv 2023年
作者: Li, Tianyu Zou, Shufan Chang, Xinghua Zhang, Laiping Deng, Xiaogang School of Computer Science Sichuan University Chengdu610065 China College of Aerospace Science and Engineering National University of Defense Technology Changsha410000 China Unmanned Systems Research Center National Innovation Institute of Defense Technology Beijing100071 China Academy of Military Sciences Beijing100190 China Tianfu Engineering-oriented Numerical Simulation & Software Innovation Center Sichuan University Chengdu610207 China
The rapid development of deep learning has significant implications for the advancement of Computational Fluid Dynamics (CFD). Currently, most pixel-grid-based deep learning methods for flow field prediction exhibit s... 详细信息
来源: 评论
Novel technique based on triangle decimation for tetrahedral simplification
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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2007年 第12期35卷 2343-2346页
作者: Wang, Xuan-Ming Wu, Ju-Ying Wu, En-Hua State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences Beijing 100080 China Air Force Engineering University Xi'an 710077 China
How to simplify a large scale tetrahedral dataset in order to use in the real time rendering is of more importance. A novel technique based on triangle decimation for tetrahedral simplification is described here. A tr... 详细信息
来源: 评论
pFedLVM: A Large Vision Model (LVM)-Driven and Latent Feature-Based Personalized Federated Learning Framework in Autonomous Driving
arXiv
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arXiv 2024年
作者: Kou, Wei-Bin Lin, Qingfeng Tang, Ming Xu, Sheng Ye, Rongguang Leng, Yang Wang, Shuai Li, Guofa Chen, Zhenyu Zhu, Guangxu Wu, Yik-Chung Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Shenzhen Research Institute of Big Data Shenzhen China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Research Institute of Electronic Science and Technology University of Electronic Science and technology Chengdu China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China State Key Laboratory for Novel Software Technology Nanjing University Nanjing China College of Mechanical and Vehicle Engineering Chongqing University Chongqing China
Deep learning-based Autonomous Driving (AD) semantic segmentation (SSeg) models often exhibit poor generalization due to data heterogeneity in an ever domain-shifting environment. While Federated Learning (FL) could i... 详细信息
来源: 评论
FedMDC: Enabling Communication-Efficient Federated Learning over Packet Lossy Networks via Multiple Description Coding
FedMDC: Enabling Communication-Efficient Federated Learning ...
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IEEE International Conference on Multimedia and Expo (ICME)
作者: Yixuan Guan Xuefeng Liu Tao Ren Jianwei Niu State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China State Key Laboratory of Intelligent Game Institute of Software Chinese Academy of Sciences Beijing China Zhengzhou University Research Institute of Industrial Technology School of Information Engineering Zhengzhou University Zhengzhou China
Federated learning (FL) generally suffers significant communication overhead from high-traffic gradient synchronization. The majority of existing studies on this problem aim at compressing gradients under the premise ... 详细信息
来源: 评论
FedTC: Enabling Communication-Efficient Federated Learning via Transform Coding
FedTC: Enabling Communication-Efficient Federated Learning v...
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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies
作者: Yixuan Guan Xuefeng Liu Jianwei Niu Tao Ren State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China Zhengzhou University Research Institute of Industrial Technology School of Information Engineering Zhengzhou University Zhengzhou China State Key Laboratory of Intelligent Game Institute of Software Chinese Academy of Sciences Beijing China
Federated learning (FL) enables distributed training via periodically synchronizing model updates among participants. Communication overhead becomes a dominant constraint of FL since participating clients usually suff... 详细信息
来源: 评论
M3OFF: Module-Compositional Model-Free Computation Offloading in Multi-Environment MEC
M3OFF: Module-Compositional Model-Free Computation Offloadin...
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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies
作者: Tao Ren Zheyuan Hu Jianwei Niu Weikun Feng Hang He State Key Laboratory of Intelligent Game Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China Zhengzhou University Research Institute of Industrial Technology School of Information Engineering Zhengzhou University Zhengzhou China
Computation offloading is one of the key issues in mobile edge computing (MEC) that alleviates the tension between user equipment's limited capabilities and mobile application's high requirements. To achieve m... 详细信息
来源: 评论