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Discovery Science : 20th International Conference, DS 2017, Kyoto, Japan, October 15-17, 2017, Proceedings

Author: Akihiro Yamamoto; Takuya Kida; Takeaki Uno; Tetsuji Kuboyama
Publisher: Cham : Springer International Publishing, 2017.
Series: Lecture notes in computer science, 10558.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book constitutes the proceedings of the 20th International Conference on Discovery Science, DS 2017, held in Kyoto, Japan, in October 2017, co-located with the International Conference on Algorithmic Learning Theory, ALT 2017. The 18 revised full papers presented together with 6 short papers and 2 invited talks in this volume were carefully reviewed and selected from 42 submissions. The scope of the conference  Read more...
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Genre/Form: Konferenzschrift
Additional Physical Format: Erscheint auch als:
Druck-Ausgabe
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Akihiro Yamamoto; Takuya Kida; Takeaki Uno; Tetsuji Kuboyama
ISBN: 9783319677866 3319677861
OCLC Number: 1011417900
Description: 1 Online-Ressource (XV, 357 Seiten 90 Illustrationen)
Series Title: Lecture notes in computer science, 10558.
Responsibility: edited by Akihiro Yamamoto, Takuya Kida, Takeaki Uno, Tetsuji Kuboyama.

Abstract:

This book constitutes the proceedings of the 20th International Conference on Discovery Science, DS 2017, held in Kyoto, Japan, in October 2017, co-located with the International Conference on Algorithmic Learning Theory, ALT 2017. The 18 revised full papers presented together with 6 short papers and 2 invited talks in this volume were carefully reviewed and selected from 42 submissions. The scope of the conference includes the development and analysis of methods for discovering scientific knowledge, coming from machine learning, data mining, intelligent data analysis, big data analysis as well as their application in various scientific domains. The papers are organized in topical sections on machine learning: online learning, regression, label classification, deep learning, feature selection, recommendation system; and knowledge discovery: recommendation system, community detection, pattern mining, misc.

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