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  Differentiable Pattern Set Mining

Fischer, J., & Vreeken, J. (2021). Differentiable Pattern Set Mining. In F. Zhu, B. C. Ooi, C. Miao, G. Cong, J. Tang, & T. Derr (Eds.), KDD '21 (pp. 383-392). New York, NY: ACM. doi:10.1145/3447548.3467348.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-652F-2 Version Permalink: https://hdl.handle.net/21.11116/0000-000C-7D65-7
Genre: Conference Paper

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This work is licensed under a Creative Commons Attribution International 4.0 License. KDD ’21, August 14–18, 2021, Virtual Event, Singapore. © 2021 Copyright held by the owner/author(s). ACM ISBN 978-1-4503-8332-5/21/08. https://doi.org/10.1145/3447548.3467348
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 Creators:
Fischer, Jonas1, Author           
Vreeken, Jilles2, Author           
Affiliations:
1Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              
2External Organizations, ou_persistent22              

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Language(s): eng - English
 Dates: 2021
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Fischer_KDD2021
DOI: 10.1145/3447548.3467348
 Degree: -

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Title: 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Place of Event: Virtual Event, Singapore
Start-/End Date: 2021-08-14 - 2021-08-18

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Title: KDD '21
  Abbreviation : KDD 2021
  Subtitle : Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
Source Genre: Proceedings
 Creator(s):
Zhu, Fieda1, Editor
Ooi, Beng Chin1, Editor
Miao, Chunyan1, Editor
Cong, Gao1, Editor
Tang, Jiliang1, Editor
Derr, Tyler1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: New York, NY : ACM
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 383 - 392 Identifier: ISBN: 978-1-4503-8332-5