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  Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning

Lahoti, P., Gummadi, K., & Weikum, G. (2022). Detecting and Mitigating Test-time Failure Risks via Model-agnostic Uncertainty Learning. In J. Bailey, P. Miettinen, Y. S. Koh, D. Tao, & X. Wu (Eds.), 21st IEEE International Conference on Data Mining (pp. 1174-1179). Piscataway, NJ: IEEE. doi:10.1109/ICDM51629.2021.00141.

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2109.04432.pdf (Preprint), 841KB
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© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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 Creators:
Lahoti, Preethi1, Author           
Gummadi, Krishna2, Author           
Weikum, Gerhard1, 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: 2021-09-0920222022
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Gummadi_ICDM21
DOI: 10.1109/ICDM51629.2021.00141
 Degree: -

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Title: 21st IEEE International Conference on Data Mining
Place of Event: Auckland, New Zealand (Virtual Conference)
Start-/End Date: 2021-12-07 - 2021-12-10

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Project name : FairSocialComputing
Grant ID : 789373
Funding program : Horizon 2020 (H2020)
Funding organization : European Commission (EC)
Project name : imPACT
Grant ID : 610150
Funding program : Funding Programme 7 (FP7)
Funding organization : European Commission (EC)

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Title: 21st IEEE International Conference on Data Mining
  Abbreviation : ICDM 2021
Source Genre: Proceedings
 Creator(s):
Bailey, James1, Editor
Miettinen, Pauli1, Editor           
Koh, Yun Sing1, Editor
Tao, Dacheng1, Editor
Wu, Xindong1, Editor
Affiliations:
1 External Organizations, ou_persistent22            
Publ. Info: Piscataway, NJ : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1174 - 1179 Identifier: ISBN: 978-1-6654-2398-4