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检索条件"机构=The Distributed and Parallel Software Laboratory"
94 条 记 录,以下是61-70 订阅
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Character feature learning for named entity recognition
Character feature learning for named entity recognition
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作者: Zeng, Ping Tan, Qingping Zhang, Haoyu Meng, Xiankai Zhang, Zhuo Xu, Jianjun Lei, Yan College of Computer National University of Defense Technology Changsha China National Key Laboratory for Parallel and Distributed Processing Changsha China School of Software Engineering Chongqing University Chongqing China
The deep neural named entity recognition model automatically learns and extracts the features of entities and solves the problem of the traditional model relying heavily on complex feature engineering and obscure prof... 详细信息
来源: 评论
JCDTA: The Data Trading Archtecture Design in JointCloud Computing  24
JCDTA: The Data Trading Archtecture Design in JointCloud Com...
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24th IEEE International Conference on parallel and distributed Systems, ICPADS 2018
作者: Yue, Xikun Wang, Huaimin Liu, Wei Li, Wei Shi, Peichang Ouyang, Xue Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology Changsha China Laboratory of Software Engineering for Complex Systems National University of Defense Technology Changsha China Troops No.75835 PLA China China
JointCloud computing is a new generation cloud computing model based on collaboration among Cloud Service Providers, making resources from multiple clouds deeply integrated., and supporting customize cloud service. To... 详细信息
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Providing Virtual Cloud for Special Purposes on Demand in JointCloud Computing Environment
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Journal of Computer Science & Technology 2017年 第2期32卷 211-218页
作者: Dong-Gang Cao Member, CCF, IEEE, Bo An Pei-Chang Shi Huai-Min Wang Key Laboratory of High Confidence Software Technologies (Peking University) Ministry of Education Beijing 100871 China National Key Laboratory for Parallel and Distributed Processing National University of Defense and Technology Changsha 410073 China
Cloud computing has been widely adopted by enterprises because of its on-demand and elastic resource usage paradigm. Currently most cloud applications are running on one single cloud. However, more and more applicatio... 详细信息
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Correction to: A compressed matrix sequence method for solving normal equations of bundle adjustment
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Machine Vision and Applications 2021年 第4期32卷 1-1页
作者: Peng, Jiaxin Liu, Jie Wei, Hua Laboratory of Software Engineering for Complex Systems School of Computer Science National University of Defense Technology Changsha China Parallel and Distributed Processing Laboratory School of Computer Science National University of Defense Technology Changsha China Algorithm Lab Changsha Morale Network Technology Co. Ltd. Changsha China Water and Land Resources Research Center of the Middle Reaches of Yangtze River School of Resources Environment Science and Engineering Hubei University of Science and Technology Xianning China
A correction to this paper has been published: https://***/10.1007/s00138-021-01222-5
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Cloud workload prediction based on workflow execution time discrepancies
arXiv
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arXiv 2018年
作者: Kecskemeti, Gabor Nemeth, Zsolt Kertesz, Attila Ranjan, Rajiv Department of Computer Science Liverpool John Moores University Laboratory of Parallel and Distributed Systems MTA SZTAKI Software Engineering Department University of Szeged School of Computing Newcastle University
Infrastructure as a service clouds hide the complexity of maintaining the physical infrastructure with a slight disadvantage: they also hide their internal working details. Should users need knowledge about these deta... 详细信息
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Learning generic diffusion processes for image restoration
arXiv
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arXiv 2018年
作者: Qiao, Peng Dou, Yong Chen, Yunjin Feng, Wensen Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology Changsha China ULSee Inc. Hangzhou China College of Computer Science & Software Engineering Shenzhen University Shenzhen China
Image restoration problems are typical ill-posed problems where the regularization term plays an important role. The regularization term learned via generative approaches is easy to transfer to various image restorati... 详细信息
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Corrigendum to “A distributed Relation Detection Approach in the Internet of Things”
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Mobile Information Systems 2019年 第1期2019卷
作者: Weiping Zhu Hongliang Lu Xiaohui Cui Jiannong Cao International School of Software Wuhan University Wuhan *** Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha *** Department of Computing Hong Kong Polytechnic University Kowloon Hong Kongpolyu.edu.hk
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Crowd intelligence in AI 2.0 era
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Frontiers of Information Technology & Electronic Engineering 2017年 第1期18卷 15-43页
作者: Wei LI Wen-jun WU Huai-min WANG Xue-qi CHENG Hua-jun CHEN Zhi-hua ZHOU Rong DING State Key Laboratory of Software Development Beihang University National Laboratory for Parallel and Distributed Processing College of ComputerNational University of Defense Technology Institute of Computing Technology Chinese Academy of Sciences College of Computer Science and Technology Zhejiang University National Key Laboratory for Novel Software Technology Nanjing University
The Internet based cyber-physical world has profoundly changed the information environment for the development of artificial intelligence(AI), bringing a new wave of AI research and promoting it into the new era of AI... 详细信息
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A distributed Relation Detection Approach in the Internet of Things
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Mobile Information Systems 2017年 第1期2017卷
作者: Zhu, Weiping Lu, Hongliang Cui, Xiaohui Cao, Jiannong International School of Software Wuhan University Wuhan China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Department of Computing Hong Kong Polytechnic University Kowloon Hong Kong
In the Internet of Things, it is important to detect the various relations among objects for mining useful knowledge. Existing works on relation detection are based on centralized processing, which is not suitable for... 详细信息
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Eunomia: Scaling Concurrent Search Trees under Contention Using HTM
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ACM SIGPLAN Notices 2017年 第8期52卷 385-399页
作者: Wang, Xin Zhang, Weihua Wang, Zhaoguo Wei, Ziyun Chen, Haibo Zhao, Wenyun Software School Fudan University China Shanghai Key Laboratory of Data Science Fudan University School of Computer Science Fudan University China Institute of Parallel and Distributed Systems Shanghai Jiao Tong University China Computer Science Department New York University United States
While hardware transactional memory (HTM) has recently been adopted to construct efficient concurrent search tree structures, such designs fail to deliver scalable performance under contention. In this paper, we first... 详细信息
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