Efficient Machine Learning Systems in Edge Cloud Environments

IF 1.6 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Journal of Web Engineering Pub Date : 2024-11-01
In-Young Ko;Michael Mrissa;Juan Manuel Murillo;Abhishek Srivastava
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Abstract

The international workshop on Big Data-Driven Edge Cloud Services (BECS) aims to provide a platform for scholars and practitioners to share their experiences and present ongoing work in developing data-driven AI applications and services within distributed computing environments, commonly referred to as the edge cloud.
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边缘云环境中的高效机器学习系统
大数据驱动的边缘云服务(BECS)国际研讨会旨在为学者和从业者提供一个平台,分享他们在分布式计算环境(通常称为边缘云)中开发数据驱动的人工智能应用和服务的经验和正在进行的工作。
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来源期刊
Journal of Web Engineering
Journal of Web Engineering 工程技术-计算机:理论方法
CiteScore
1.80
自引率
12.50%
发文量
62
审稿时长
9 months
期刊介绍: The World Wide Web and its associated technologies have become a major implementation and delivery platform for a large variety of applications, ranging from simple institutional information Web sites to sophisticated supply-chain management systems, financial applications, e-government, distance learning, and entertainment, among others. Such applications, in addition to their intrinsic functionality, also exhibit the more complex behavior of distributed applications.
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