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cs.LG2026
Defensive Boosting for Online Probabilistic Forecasting
Georgy Noarov, Aaron Roth
We study online probabilistic forecasting of binary outcomes chosen by an adaptive adversary. Given an online learning algorithm for a weak hypothesis class , we would like to e…
cs.LG2026
Optimal Deterministic Multicalibration and Omniprediction
Georgy Noarov, Aaron Roth
A model is multicalibrated on a collection of group weights if it is calibrated -- i.e. unbiased even conditional on its prediction -- not just overall, but also after reweight…
cs.GT2026
Prior-Agnostic Incentive-Compatible Exploration
Ramya Ramalingam, Osbert Bastani, Aaron Roth
In bandit settings, optimizing long-term regret metrics requires exploration, which corresponds to sometimes taking myopically sub-optimal actions. When a long-lived principal mere…