Robotics & Machine Learning Daily News2024,Issue(MAY.17) :67-68.

Investigators at South China University of Technology Discuss Findings in Comput ational Intelligence (Time-sensitive Federated Learning With Heterogeneous Train ing Intensity: a Deep Reinforcement Learning Approach)

Robotics & Machine Learning Daily News2024,Issue(MAY.17) :67-68.

Investigators at South China University of Technology Discuss Findings in Comput ational Intelligence (Time-sensitive Federated Learning With Heterogeneous Train ing Intensity: a Deep Reinforcement Learning Approach)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Machine Learning - Com putational Intelligence is the subject of a report. According to news reporting out of Guangzhou, People’s Republic of China, by NewsRx editors, research stated , “Federated learning (FL) has recently received sufficient attention because of its capability of collaboratively training machine learning models without expo sing data privacy. Most existing FL schemes assume the fixed or predetermined lo cal training intensities/iterations at clients for each communication round, whi ch however neglects the effect of local training intensity determination on the performance of FL.”

Key words

Guangzhou/People’s Republic of China/Asia/Computational Intelligence/Emerging Technologies/Machine Learning/Reinfo rcement Learning/South China University of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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