Robotics & Machine Learning Daily News2024,Issue(Nov.1) :55-56.

Researchers at University of New South Wales Have Reported New Data on Machine L earning (Accelerating Communication-efficient Federated Multi-task Learning With Personalization and Fairness)

Robotics & Machine Learning Daily News2024,Issue(Nov.1) :55-56.

Researchers at University of New South Wales Have Reported New Data on Machine L earning (Accelerating Communication-efficient Federated Multi-task Learning With Personalization and Fairness)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – New research on Machine Learning is the subject o f a report. According to news reporting originating from Sydney, Australia, by N ewsRx correspondents, research stated, “Federated learning techniques provide a promising framework for collaboratively training a machine learning model withou t sharing users’ data, and delivering a security solution to guarantee privacy d uring the model training of IoT devices. Nonetheless, challenges posed by data h eterogeneity and communication resource constraints make it difficult to develop an efficient federated learning algorithm in terms of the low order of converge nce rate.”

Key words

Sydney/Australia/Australia and New Zea land/Algorithms/Cyborgs/Emerging Technologies/Machine Learning/University o f New South Wales

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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