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cs.LG2024
SCOD: From Heuristics to Theory
Vojtech Franc, Jakub Paplham, Daniel Prusa
This paper addresses the problem of designing reliable prediction models that abstain from predictions when faced with uncertain or out-of-distribution samples - a recently propose…
cs.LG2023
Reject option models comprising out-of-distribution detection
Vojtech Franc, Daniel Prusa, Jakub Paplham
The optimal prediction strategy for out-of-distribution (OOD) setups is a fundamental question in machine learning. In this paper, we address this question and present several cont…
cs.LG2021★ 6 cited
Optimal strategies for reject option classifiers
V. Franc, D. Prusa, V. Voracek
In classification with a reject option, the classifier is allowed in uncertain cases to abstain from prediction. The classical cost-based model of a reject option classifier requir…