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multicalibration
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multicalibration-f1d71036·1 events·first seen 47h agoAliases: multicalibration
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model calibrationOptimal Deterministic Multicalibration and OmnipredictionExpected Calibration ErrorUncertainty Calibrationdifferentiable dynamics sensor calibrationHuman-AI Teaming Through the Lens of CalibrationCalibrated SurpriseUniCAD-MLLMPhi4-Multimodalmultimodal meta-verificationmultilingual mathematical benchmarksMultimodal Continual Instruction Tuning
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Optimal deterministic multicalibration achieved, resolving open problem on randomization necessity
A new arXiv preprint resolves an open problem in multicalibration theory by constructing a minimax-optimal multicalibration algorithm that outputs a deterministic predictor, achieving the same O(ε⁻³) sample complexity previously only attainable by randomized predictors. The result extends to outcome indistinguishability, deterministic omnipredictors, and panpredictors with optimal sample complexity, resolving multiple open problems from recent works. Multicalibration is a fairness and reliability property requiring calibration to hold across reweighted subgroups, making this relevant to trustworthy ML research.