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Konstantina Bairaktari

2 accepted papers

2025

Kandinsky Conformal Prediction: Beyond Class- and Covariate-Conditional Coverage

ICML 2025poster

Conformal prediction is a powerful distribution-free framework for constructing prediction sets with coverage guarantees. Classical methods, such as split conformal prediction, provide marginal coverage, ensuring that the prediction set contains the label of a random test point with a target probabi…

Cited by 0SourcePDFScholar
2025

Privacy in Metalearning and Multitask Learning: Modeling and Separations

AISTATS 2025poster

Model personalization allows a set of individuals, each facing a different learning task, to train models that are more accurate for each person than those they could develop individually. The goals of personalization are captured in a variety of formal frameworks, such as multitask learning and met…

Cited by 0SourceScholar