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Sequential Covariate Shift Detection Using Classifier Two-Sample Tests
This problem can naturally be solved using a two-sample test--- i. e., test whether the current test distribution of covariates equals the training distribution of covariates.
Confidence Calibration with Bounded Error Using Transformations
As machine learning techniques become widely adopted in new domains, especially in safety-critical systems such as autonomous vehicles, it is crucial to provide accurate output uncertainty estimation.
Improving Classifier Confidence using Lossy Label-Invariant Transformations
Providing reliable model uncertainty estimates is imperative to enabling robust decision making by autonomous agents and humans alike.
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