Rank-based conformal scores make changepoint localization sets finite-sample valid for any frozen weights and exactly invariant to monotone data transforms, transferring certified set lengths across the entire monotone orbit.
Offline changepoint localization using a matrix of conformal p-values.Transactions on Machine Learning Research, 2026
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ARC: Augmented-Rank Conformalization for Changepoint Localization --- Finite-Sample Validity and Distribution-Robust Efficiency
Rank-based conformal scores make changepoint localization sets finite-sample valid for any frozen weights and exactly invariant to monotone data transforms, transferring certified set lengths across the entire monotone orbit.