13 citations · 18 across the 5 of their papers we have counts for
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cs.LG2022★ 13 cited
TRUST-LAPSE: An Explainable and Actionable Mistrust Scoring Framework for Model Monitoring
Nandita Bhaskhar, Daniel L. Rubin, Christopher Lee-Messer
Continuous monitoring of trained ML models to determine when their predictions should and should not be trusted is essential for their safe deployment. Such a framework ought to be…
cs.LG2021
Double Descent Optimization Pattern and Aliasing: Caveats of Noisy Labels
Florian Dubost, Erin Hong, Max Pike +5
Optimization plays a key role in the training of deep neural networks. Deciding when to stop training can have a substantial impact on the performance of the network during inferen…