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Titlebook: Cloud Computing – CLOUD 2022; 15th International C Kejiang Ye,Liang-Jie Zhang Conference proceedings 2022 The Editor(s) (if applicable) and

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書目名稱Cloud Computing – CLOUD 2022
副標題15th International C
編輯Kejiang Ye,Liang-Jie Zhang
視頻videohttp://file.papertrans.cn/229/228461/228461.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Cloud Computing – CLOUD 2022; 15th International C Kejiang Ye,Liang-Jie Zhang Conference proceedings 2022 The Editor(s) (if applicable) and
描述This book constitutes the proceedings of the 15th International Conference on Cloud Computing, CLOUD 2022, held as part of the Services Conference Federation, SCF 2022, held in Honolulu, HI, USA, in December 2022.?.The 8 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 15 submissions..The International Conference on Cloud Computing (CLOUD) has been a prime international forum for both researchers and industry practitioners to exchange the latest fundamental advances in the state of the art and practice of cloud computing, identify emerging research topics, and define the future of cloud computing. All topics regarding cloud computing align with the theme of CLOUD..
出版日期Conference proceedings 2022
關鍵詞artificial intelligence; cloud computing; commerce; communication systems; computer networks; computer sy
版次1
doihttps://doi.org/10.1007/978-3-031-23498-9
isbn_softcover978-3-031-23497-2
isbn_ebook978-3-031-23498-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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,Towards an?Efficient Client Selection System for?Federated Learning,completion of model training or evaluation without sharing private or local data. More and more modern data applications turn to federated learning models due to their scalability and privacy preservation. Selecting proper clients for model training and evaluation is a key issue for federated learni
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,Hestia: A Cost-Effective Multi-dimensional Resource Utilization for?Microservices Execution in?the?e cluster, if each machine can save a small amount of resources, a huge effect could be made to significantly reduce the overall computing cost as the saved resources across the cluster can be gathered into a large resource pool to facilitate the computation as a whole. As such, how to effectively a
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Analysis of Data Micro-governance in Full Life Cycle Management of the Leased Assets, things are applied to the full life cycle management of leased assets. And combined with the theoretical knowledge framework of DAMA data management system, which making data management ideas and methods are practiced in the online asset management platform project. This study considerably provides
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https://doi.org/10.1007/978-3-658-45377-0loss (CL) as an auxiliary supervision for the meta-training stage. The proposed bipartite method, called FSIC-SSL, can SOTA task accuracies on two mainstream FSIC benchmark datasets. Our code will be available at ..
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