Advanced Analytics and Learning on Temporal Data: 4th Ecml Pkdd Workshop, Aaltd 2019, Würzburg, Germany, September 20, 2019, Revised Selected Papers
暫譯: 時間數據的進階分析與學習:第四屆 ECML PKDD 研討會,AALTD 2019,德國維爾茨堡,2019年9月20日,修訂選定論文

Lemaire, Vincent, Malinowski, Simon, Bagnall, Anthony

  • 出版商: Springer
  • 出版日期: 2020-01-23
  • 售價: $2,310
  • 貴賓價: 9.5$2,195
  • 語言: 英文
  • 頁數: 229
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3030390977
  • ISBN-13: 9783030390976
  • 海外代購書籍(需單獨結帳)

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商品描述

This book constitutes the refereed proceedings of the 4th ECML PKDD Workshop on Advanced Analytics and Learning on Temporal Data, AALTD 2019, held in W rzburg, Germany, in September 2019.
The 7 full papers presented together with 9 poster papers were carefully reviewed and selected from 31 submissions. The papers cover topics such as temporal data clustering; classification of univariate and multivariate time series; early classification of temporal data; deep learning and learning representations for temporal data; modeling temporal dependencies; advanced forecasting and prediction models; space-temporal statistical analysis; functional data analysis methods; temporal data streams; interpretable time-series analysis methods; dimensionality reduction, sparsity, algorithmic complexity and big data challenge; and bio-informatics, medical, energy consumption, on temporal data.

商品描述(中文翻譯)

本書是2019年9月在德國維爾茲堡舉行的第四屆ECML PKDD關於時間數據的高級分析與學習工作坊(AALTD 2019)的經過審稿的會議論文集。共提交了31篇論文,經過仔細審查後,選出了7篇完整論文和9篇海報論文。這些論文涵蓋的主題包括:時間數據聚類;單變量和多變量時間序列的分類;時間數據的早期分類;時間數據的深度學習和學習表示;建模時間依賴性;高級預測和預測模型;時空統計分析;功能數據分析方法;時間數據流;可解釋的時間序列分析方法;維度減少、稀疏性、算法複雜性和大數據挑戰;以及生物信息學、醫療、能源消耗等時間數據相關的主題。

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