Robotics & Machine Learning Daily News2024,Issue(Apr.29) :107-108.

Researchers from China Coal Research Institute Describe Findings in Machine Lear ning (Energy or Accuracy? Near-optimal User Selection and Aggregator Placement f or Federated Learning In Mec)

Robotics & Machine Learning Daily News2024,Issue(Apr.29) :107-108.

Researchers from China Coal Research Institute Describe Findings in Machine Lear ning (Energy or Accuracy? Near-optimal User Selection and Aggregator Placement f or Federated Learning In Mec)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Current study results on Machine Learning have be en published. According to news originatingfrom Ningxia, People’s Republic of C hina, by NewsRx correspondents, research stated, “To unveil thehidden value in the datasets of user equipments (UEs) while preserving user privacy, federated l earning(FL) is emerging as a promising technique to train a machine learning mo del using the datasets of UEslocally without uploading the datasets to a centra l location. Customers require to train machine learningmodels based on differen t datasets of UEs, through issuing FL requests that are implemented by FL services in a mobile edge computing (MEC) network.”

Key words

Ningxia/People’s Republic of China/Asi a/Algorithms/Cyborgs/Emerging Technologies/Machine Learning/China Coal Rese arch Institute

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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