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 折 $2,290
- 語言: 英文
- 頁數: 852
- 裝訂: Paperback
- ISBN: 3319712489
- ISBN-13: 9783319712482
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相關分類:
Machine Learning、Computer-Science、資料庫
海外代購書籍(需單獨結帳)
相關主題
商品描述
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。