Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part I (Lecture Notes in Computer Science)

  • 出版商: Springer
  • 出版日期: 2017-12-30
  • 售價: $2,410
  • 貴賓價: 9.5$2,290
  • 語言: 英文
  • 頁數: 852
  • 裝訂: Paperback
  • ISBN: 3319712489
  • ISBN-13: 9783319712482
  • 相關分類: Machine LearningComputer-Science資料庫
  • 海外代購書籍(需單獨結帳)

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商品描述

The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. 

The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions; there are 47 papers in the applied data science, nectar and demo track. 

The contributions were organized in topical sections named as follows:
Part I: anomaly detection; computer vision; ensembles and meta learning; feature selection and extraction; kernel methods; learning and optimization, matrix and tensor factorization; networks and graphs; neural networks and deep learning.
Part II: pattern and sequence mining; privacy and security; probabilistic models and methods; recommendation; regression; reinforcement learning; subgroup discovery; time series and streams; transfer and multi-task learning; unsupervised and semisupervised learning.
Part III: applied data science track; nectar track; and demo track.

商品描述(中文翻譯)

這三卷的會議論文集 LNAI 10534 – 10536 是2017年9月在馬其頓斯科普里舉行的歐洲機器學習與數據庫知識發現會議(ECML PKDD 2017)的經過審核的會議論文集。

第一部分和第二部分共計101篇常規論文,這些論文是從364篇投稿中仔細審核和選出的;在應用數據科學、nectar和演示專題中有47篇論文。

這些貢獻被組織成以下主題部分:
第一部分:異常檢測;計算機視覺;集成學習和元學習;特徵選擇和提取;核方法;學習和優化,矩陣和張量分解;網絡和圖;神經網絡和深度學習。
第二部分:模式和序列挖掘;隱私和安全;概率模型和方法;推薦;回歸;強化學習;子群發現;時間序列和流;轉移學習和多任務學習;無監督和半監督學習。
第三部分:應用數據科學專題;nectar專題;以及演示專題。

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