arXiv Machine Learning July 23, 2026 By Lunjia Hu, Kevin Tian, Chutong Yang

Optimal Recalibration of an Online Predictor

Read the original on arXiv Machine Learning →

arXiv:2607. 19689v1 Announce Type: cross Abstract: We study the problem of recalibrating an online predictor [KE17, OKS24]: given an arbitrary "hint" sequence of forecasts, the learner must output new predictions that are calibrated while incurring small excess error relative to the original forecasts, under a proper loss.

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