Robotics & Machine Learning Daily News2024,Issue(Dec.6) :53-54.

Researchers from Massachusetts Institute of Technology Report Recent Findings in Robotics and Automation (Model Free Method of Screening Training Data for Adver sarial Datapoints Through Local Lipschitz Quotient Analysis)

麻省理工学院的研究人员报告了机器人和自动化的最新发现(通过局部Lipschitz商分析筛选Adver sarial数据点的训练数据的无模型方法)

Robotics & Machine Learning Daily News2024,Issue(Dec.6) :53-54.

Researchers from Massachusetts Institute of Technology Report Recent Findings in Robotics and Automation (Model Free Method of Screening Training Data for Adver sarial Datapoints Through Local Lipschitz Quotient Analysis)

麻省理工学院的研究人员报告了机器人和自动化的最新发现(通过局部Lipschitz商分析筛选Adver sarial数据点的训练数据的无模型方法)

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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-机器人-机器人和自动化的最新数据在一份新的报告中呈现。根据NewsRx编辑在马萨诸塞州Cam Bridge的新闻报道,研究表明,“这是为学习问题选择合适的数据特征经常遇到挑战。有时某些规则数据更难学习,因为它们没有被选定的数据特征很好地描述。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Fresh data on Robotics - Robotics and Automation are presented in a new report.According to news reporting out of Cam bridge, Massachusetts, by NewsRx editors, research stated, “It isoften challeng ing to pick suitable data features for learning problems. Sometimes certain regi ons of thedata are harder to learn because they are not well characterized by t he selected data features.”

Key words

Cambridge/Massachusetts/United States/North and Central America/Robotics and Automation/Robotics/Risk and Preventi on/Massachusetts Institute of Technology

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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