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Robust Decision Making with Partially Calibrated Forecasts
Shayan Kiyani, Hamed Hassani, George Pappas +1
Calibration has emerged as a foundational goal in ``trustworthy machine learning'', in part because of its strong decision theoretic semantics. Independent of the underlying distri…
The Relationship between No-Regret Learning and Online Conformal Prediction
Ramya Ramalingam, Shayan Kiyani, Aaron Roth
Existing algorithms for online conformal prediction -- guaranteeing marginal coverage in adversarial settings -- are variants of online gradient descent (OGD), but their analyses o…
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents
Shayan Kiyani, George Pappas, Aaron Roth +1
A fundamental question in data-driven decision making is how to quantify the uncertainty of predictions in ways that can usefully inform downstream action. This interface between p…