首页|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)
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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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.”
NingxiaPeople’s Republic of ChinaAsi aAlgorithmsCyborgsEmerging TechnologiesMachine LearningChina Coal Rese arch Institute
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