Robotics & Machine Learning Daily News2024,Issue(Dec.5) :117-117.

Findings from Central South University Provide New Insights into Intelligent Sys tems (FL-Joint: joint aligning features and labels in federated learning for dat a heterogeneity)

中南大学的研究结果为智能系统TEM提供了新的见解(FL-Joint:针对DAT A异构性联合学习中的功能和标签联合对齐)

Robotics & Machine Learning Daily News2024,Issue(Dec.5) :117-117.

Findings from Central South University Provide New Insights into Intelligent Sys tems (FL-Joint: joint aligning features and labels in federated learning for dat a heterogeneity)

中南大学的研究结果为智能系统TEM提供了新的见解(FL-Joint:针对DAT A异构性联合学习中的功能和标签联合对齐)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-关于智能系统的详细数据已经呈现。根据新闻报道由NewsRx通讯员从中南大学发起,研究称,“联邦学习”是一种分布式的机器学习范式,它使用来自不同客户端的数据来训练共享模型DIV ERSE客户端设置和环境带来的数据异构性核心挑战。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on intelligent systems h ave been presented. According to news reportingoriginating from Central South U niversity by NewsRx correspondents, research stated, “Federated learningis a di stributed machine learning paradigm that trains a shared model using data from v arious clients, itfaces a core challenge in data heterogeneity arising from div erse client settings and environments.”

Key words

Central South University/Intelligent Sy stems/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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