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Titlebook: Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference; Rashid Mehmood,Victor Alves,Michela

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書目名稱Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference
編輯Rashid Mehmood,Victor Alves,Michela Ricca
視頻videohttp://file.papertrans.cn/282/281815/281815.mp4
概述Highlights the latest research on distributed computing and artificial intelligence.Presents the outcomes of the special sessions of the 20th DCAI.Written by respected experts in the field
叢書名稱Lecture Notes in Networks and Systems
圖書封面Titlebook: Distributed Computing and Artificial Intelligence, Special Sessions I, 20th International Conference;  Rashid Mehmood,Victor Alves,Michela
描述.The present book brings together experience, current work, and promising future trends associated with distributed computing, artificial intelligence, and their application in order to provide efficient solutions to real problems. DCAI 2023 is a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing areas. This year’s technical program presents both high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 108 papers were submitted, by authors from 31 different countries representing a truly “wide area network” of research activity. The DCAI’23 technical program has selected 50 full papers in the Special Sessions (ASET, AIMPM, AI4CS, CLIRAI, TECTONIC, PSO-ML, SmartFoF, IoTalentum) and, as in past editions, it will be special issues in ranked journals. This symposium is organized by the LASI and Centro Algoritmi of the University of Minho (Portugal). The authors like to thank all the contributing authors, the members of the Program Committee, National Associations (AEPIA, APPIA), and the sponsors (AIR Institute)..
出版日期Conference proceedings 2023
關(guān)鍵詞Intelligent Computing; Distributed Computing; Computational Intelligence; Artificial Intelligence; DCAI2
版次1
doihttps://doi.org/10.1007/978-3-031-38318-2
isbn_softcover978-3-031-38317-5
isbn_ebook978-3-031-38318-2Series ISSN 2367-3370 Series E-ISSN 2367-3389
issn_series 2367-3370
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Massive Natural Language Processing in?Distributed Environmentt and the accuracy of the predictions in relation to the scale of the distributions. The results clearly show that an increase in performance can be obtained without a significant decrease in accuracy.
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