Robotics & Machine Learning Daily News2024,Issue(Jun.12) :31-32.

Researchers from State University of New York (SUNY) Albany Report Findings in Machine Learning (Differentially Private Stochastic Gradient Descent With Low-noise)

来自纽约州立大学(SUNY)奥尔巴尼分校的研究人员报告了机器学习的发现(低噪声差异私人随机梯度下降)

Robotics & Machine Learning Daily News2024,Issue(Jun.12) :31-32.

Researchers from State University of New York (SUNY) Albany Report Findings in Machine Learning (Differentially Private Stochastic Gradient Descent With Low-noise)

来自纽约州立大学(SUNY)奥尔巴尼分校的研究人员报告了机器学习的发现(低噪声差异私人随机梯度下降)

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摘要

由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-机器学习的新数据在一份新的报告中呈现。根据来自纽约奥尔巴尼的NewSRX记者的新闻报道,研究表明:“现代机器学习算法旨在从数据中提取细粒度的信息以提供准确的预测,而这往往与隐私保护的目标相冲突。本文讨论了开发隐私保护机器学习算法的实践和理论重要性,该算法在保证良好性能的同时保护隐私。”

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Fresh data on Machine Learning are presented in a new report. According to news reporting originating from Albany, New York, by N ewsRx correspondents, research stated, “Modern machine learning algorithms aim t o extract fine-grained information from data to provide accurate predictions, wh ich often conflicts with the goal of privacy protection. This paper addresses the practical and theoretical importance of developing privacy -preserving machine learning algorithms that ensure good performance while preserving privacy.”

Key words

Albany/New York/United States/North a nd Central America/Algorithms/Cyborgs/Emerging Technologies/Machine Learning/State University of New York (SUNY) Albany

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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