A mechanism using semivalues and unknown validation sets provably ensures collaborative fairness and truthfulness at equilibrium for Bayesian models.
IEEE 18th International Symposium on Biomedical Imaging (ISBI) , pages=
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StCP leverages transfer learning to stabilize the size of conformal prediction sets without additional target labels.
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Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
A mechanism using semivalues and unknown validation sets provably ensures collaborative fairness and truthfulness at equilibrium for Bayesian models.
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Stable Localized Conformal Prediction via Transduction
StCP leverages transfer learning to stabilize the size of conformal prediction sets without additional target labels.