Machine Learning and Knowledge Discovery in Databases: European Conference, Ecml Pkdd 2019, Würzburg, Germany, September 16-20, 2019, Proceedings, Par
暫譯: 機器學習與資料庫中的知識發現:歐洲會議,ECML PKDD 2019,德國維爾茨堡,2019年9月16-20日,會議論文集

Brefeld, Ulf, Fromont, Elisa, Hotho, Andreas

  • 出版商: Springer
  • 出版日期: 2020-05-01
  • 售價: $2,400
  • 貴賓價: 9.5$2,280
  • 語言: 英文
  • 頁數: 804
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 3030461327
  • ISBN-13: 9783030461324
  • 相關分類: Machine Learning資料庫
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

The three volume proceedings LNAI 11906 - 11908 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2019, held in W rzburg, Germany, in September 2019.

The total of 130 regular papers presented in these volumes was carefully reviewed and selected from 733 submissions; there are 10 papers in the demo track.

The contributions were organized in topical sections named as follows:

Part I: pattern mining; clustering, anomaly and outlier detection, and autoencoders; dimensionality reduction and feature selection; social networks and graphs; decision trees, interpretability, and causality; strings and streams; privacy and security; optimization.

Part II: supervised learning; multi-label learning; large-scale learning; deep learning; probabilistic models; natural language processing.

Part III: reinforcement learning and bandits; ranking; applied data science: computer vision and explanation; applied data science: healthcare; applied data science: e-commerce, finance, and advertising; applied data science: rich data; applied data science: applications; demo track.

商品描述(中文翻譯)

這三卷的會議論文集 LNAI 11906 - 11908 是 2019 年歐洲機器學習與資料庫知識發現會議(ECML PKDD 2019)的經過審核的論文集,該會議於 2019 年 9 月在德國維爾茲堡舉行。

這些卷中共呈現了 130 篇常規論文,這些論文是從 733 篇投稿中仔細審核和選出的;此外,還有 10 篇來自演示軌道的論文。

這些貢獻被組織成以下主題部分:

第一部分:模式挖掘;聚類、異常和離群點檢測,以及自編碼器;降維和特徵選擇;社交網絡和圖形;決策樹、可解釋性和因果關係;字串和流;隱私和安全;優化。

第二部分:監督學習;多標籤學習;大規模學習;深度學習;概率模型;自然語言處理。

第三部分:強化學習和賭徒;排序;應用數據科學:計算機視覺和解釋;應用數據科學:醫療保健;應用數據科學:電子商務、金融和廣告;應用數據科學:豐富數據;應用數據科學:應用;演示軌道。

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