Robotics & Machine Learning Daily News2024,Issue(Nov.1) :31-31.

Findings from University of St Andrews Provide New Insights into Machine Learnin g (Pipar: : Pipeline Parallelism for Collaborative Machine Learning)

Robotics & Machine Learning Daily News2024,Issue(Nov.1) :31-31.

Findings from University of St Andrews Provide New Insights into Machine Learnin g (Pipar: : Pipeline Parallelism for Collaborative Machine Learning)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news originating from St. Andrews, United Kingdom, by NewsRx correspondents, research stated, “Collaborative machine learn ing (CML) techniques, such as federated learning, have been proposed to train de ep learning models across multiple mobile devices and a server. CML techniques a re privacy-preserving as a local model that is trained on each device instead of the raw data from the device is shared with the server.” Financial support for this research came from Rakuten Mobile, Inc., Japan.

Key words

St. Andrews/United Kingdom/Europe/Cyb orgs/Emerging Technologies/Machine Learning/University of St Andrews

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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