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Machine Learning From Distributed, Streaming Data [From the Guest Editors]
IEEE Signal Processing Magazine ( IF 14.9 ) Pub Date : 2020-05-01 , DOI: 10.1109/msp.2020.2972654
Waheed U. Bajwa , Volkan Cevher , Dimitris Papailiopoulos , Anna Scaglione

The articles in this special section focus on machine learning from distributed, streaming media. The field of machine learning has undergone radical transformations during the last decade. These transformations, which have been fueled by our ability to collect and generate tremendous volumes of training data and leverage massive amounts of lowcost computing power, have led to an explosion in research activity in the field by academic and industrial researchers. Discusses the fields that are adopting machine learning and reports on applications for their use.

中文翻译:

从分布式流数据中进行机器学习 [来自客座编辑]

此特殊部分中的文章侧重于从分布式流媒体中进行机器学习。在过去的十年中,机器学习领域发生了根本性的转变。我们收集和生成大量训练数据的能力以及利用大量低成本计算能力的能力推动了这些转变,导致学术和工业研究人员在该领域的研究活动激增。讨论采用机器学习的领域并报告其使用的应用程序。
更新日期:2020-05-01
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