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  Learning Linear Temporal Properties from Noisy Data: A MaxSAT-Based Approach

Gaglione, J.-R., Neider, D., Roy, R., Topcu, U., & Xu, Z. (2021). Learning Linear Temporal Properties from Noisy Data: A MaxSAT-Based Approach. In Z. Hou, & V. Ganesh (Eds.), Automated Technology for Verification and Analysis (pp. 74-90). Berlin: Springer. doi:10.1007/978-3-030-88885-5_6.

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Item Permalink: https://hdl.handle.net/21.11116/0000-0009-6D26-3 Version Permalink: https://hdl.handle.net/21.11116/0000-0009-6D27-2
Genre: Conference Paper
Latex : Learning Linear Temporal Properties from Noisy Data: {A} {MaxSAT}-Based Approach

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 Creators:
Gaglione, Jean-Raphaël1, Author
Neider, Daniel2, Author           
Roy, Rajarshi2, Author           
Topcu, Ufuk1, Author
Xu, Zhe1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Group R. Majumdar, Max Planck Institute for Software Systems, Max Planck Society, ou_2105292              

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Language(s): eng - English
 Dates: 20212021
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Gaglione_ATVA21
DOI: 10.1007/978-3-030-88885-5_6
 Degree: -

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Title: 19th International Symposium on Automated Technology for Verification and Analysis
Place of Event: Gold Coast, Australia
Start-/End Date: 2021-10-18 - 2021-10-22

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Title: Automated Technology for Verification and Analysis
  Abbreviation : ATVA 2021
  Subtitle : 19th International Symposium, ATVA 2021 ; Gold Coast, QLD, Australia, October 18–22, 2021 ; Proceedings
Source Genre: Proceedings
 Creator(s):
Hou, Zhe1, Editor
Ganesh, Vijay1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: Berlin : Springer
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 74 - 90 Identifier: ISBN: 978-3-030-88884-8

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Title: Lecture Notes in Computer Science
  Abbreviation : LNCS
Source Genre: Series
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Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 12971 Sequence Number: - Start / End Page: - Identifier: -