Robotics & Machine Learning Daily News2024，Issue(Dec.2) ：26-26.

Study Results from Nanjing University Broaden Understanding of Machine Learning (Rts: Learning Robustly From Time Series Data With Noisy Label)

南京大学的研究成果拓宽了机器学习的理解(Rts:从带噪声标签的时间序列数据中稳健学习)

Robotics & Machine Learning Daily News2024，Issue(Dec.2) ：26-26.
✕
  • NETL
  • NSTL

Study Results from Nanjing University Broaden Understanding of Machine Learning (Rts: Learning Robustly From Time Series Data With Noisy Label)

南京大学的研究成果拓宽了机器学习的理解(Rts:从带噪声标签的时间序列数据中稳健学习)

扫码查看

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-关于机器学习的最新研究结果已经发表。据新闻报道研究称，NewsRx记者源于中华人民共和国南京的报道，“在机器学习中，大量干净的标签和静态的标签已经取得了重大进展。”数据。然而,在许多实际应用中,数据往往随着时间的推移而发生变化,很难对数据进行实时处理获得大量干净的注释，即噪音标签和时间序列同时面对。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Current study results on Machine Learn ing have been published. According to newsreporting originating in Nanjing, Peo ple’s Republic of China, by NewsRx journalists, research stated,“Significant pr ogress has been made in machine learning with large amounts of clean labels and staticdata. However, in many real-world applications, the data often changes wi th time and it is difficult toobtain massive clean annotations, that is, noisy labels and time series are faced simultaneously.”

Key words

Nanjing/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/Nanjing University

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN：
段落导航相关论文