A new algorithm achieves minimax-optimal sample complexity for multicalibration using deterministic predictors, resolving a long-standing open problem. The method also produces deterministic predictors that satisfy outcome indistinguishability and enables optimal deterministic omnipredictors and panpredictors, addressing open questions from prior works.
Deterministic Multicalibration with Optimal Sample Complexity
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