Topic Signal: Batch Multicalibration: In sample convergence and out-of-sample generalization. A bucketed definition of multicalibration for real valued predictors, and a sequential algorithm that guarantees multicalibration ...
Cis 7000 Modern Topics In Uncertainty Quantification Lecture 9 - Research Notes for Readers
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Research Notes for Readers
Sequential mean and quantile calibration against an adversary, beginning with a solution to the homework from last We gave two algorithms to obtain group conditional mean consistency, for an arbitrary set of ... We think about using models on distributions that differ from the distributions that they have been trained on.
Helpful Points for Readers
We think about using models on distributions that differ from the distributions that they have been trained on. A bucketed definition of multicalibration for real valued predictors, and a sequential algorithm that guarantees multicalibration ...
Context Comparison Context
We introduce the problem of conformal prediction, which reduces the problem of producing prediction sets to the problem of ... Batch Multicalibration: In sample convergence and out-of-sample generalization. Multicalibration with respect to real valued functions, and a view of multicalibration as a boosting algorithm for regression.
Context Follow-Up Tips
Multicalibration with respect to real valued functions, and a view of multicalibration as a boosting algorithm for regression.
Relevant points collected here
- Multicalibration with respect to real valued functions, and a view of multicalibration as a boosting algorithm for regression.
- Batch Multicalibration: In sample convergence and out-of-sample generalization.
- We introduce the problem of conformal prediction, which reduces the problem of producing prediction sets to the problem of ...
- A bucketed definition of multicalibration for real valued predictors, and a sequential algorithm that guarantees multicalibration ...
- We think about using models on distributions that differ from the distributions that they have been trained on.
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