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cs.LG2024
Breaking the Barrier for Sequential Calibration
Yuval Dagan, Constantinos Daskalakis, Maxwell Fishelson +3
A set of probabilistic forecasts is calibrated if each prediction of the forecaster closely approximates the empirical distribution of outcomes on the subset of timesteps where tha…
cs.LG2024
Omnipredictors for Regression and the Approximate Rank of Convex Functions
Parikshit Gopalan, Princewill Okoroafor, Prasad Raghavendra +2
Consider the supervised learning setting where the goal is to learn to predict labels given points from a distribution. An \textit{omnipredictor} for a clas…