边缘云中多模型联合学习的联合参与者选择与学习优化

IF 1.2 3区计算机科学 Q4 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE

Journal of Computer Science and Technology Pub Date : 2023-07-01 DOI:10.1007/s11390-023-3074-4

Xinliang Wei, Jiyao Liu, Yu Wang

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Joint Participant Selection and Learning Optimization for Federated Learning of Multiple Models in Edge Cloud

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来源期刊

Journal of Computer Science and Technology 工程技术-计算机：软件工程

CiteScore

4.00

自引率

0.00%

发文量

2255

审稿时长

9.8 months

期刊介绍： Journal of Computer Science and Technology (JCST), the first English language journal in the computer field published in China, is an international forum for scientists and engineers involved in all aspects of computer science and technology to publish high quality and refereed papers. Papers reporting original research and innovative applications from all parts of the world are welcome. Papers for publication in the journal are selected through rigorous peer review, to ensure originality, timeliness, relevance, and readability. While the journal emphasizes the publication of previously unpublished materials, selected conference papers with exceptional merit that require wider exposure are, at the discretion of the editors, also published, provided they meet the journal''s peer review standards. The journal also seeks clearly written survey and review articles from experts in the field, to promote insightful understanding of the state-of-the-art and technology trends. Topics covered by Journal of Computer Science and Technology include but are not limited to: -Computer Architecture and Systems -Artificial Intelligence and Pattern Recognition -Computer Networks and Distributed Computing -Computer Graphics and Multimedia -Software Systems -Data Management and Data Mining -Theory and Algorithms -Emerging Areas