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Conference Paper

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

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Lahoti,  Preethi
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Weikum,  Gerhard
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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2109.04432.pdf
(Preprint), 841KB

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Citation

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.


Cite as: https://hdl.handle.net/21.11116/0000-000A-5E15-6
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