We study distribution-free uncertainty quantification for a changepoint estimate in an offline setting. We observe a sequence with a single changepoint and are given an estimate of its location. The pre- and post-change segments are independent and each consists of i.i.d. (or, more generally, exchangeable) observations...
Multi-Source Randomly Localized Conformal Prediction is proposed, which builds on the local coverage properties of randomly localized conformal prediction and extends it to multiple sources through data-adaptive source selection and establishes finite-sample coverage bounds using an interpretable notion of envelope dis...
The Conformal LOwer bound on Changepoint Count (CLOCC) is shown to be the only feasible way to provide a lower bound on K under the stated assumptions, a property it is referred to as its universality.
In this work, we study the problem of testing conditional independence between random variables $X$ and $Y$ given a confounder $Z$. The local permutation test (LPT) offers a principled approach to this problem by partitioning the $Z$-space into pre-specified bins, and permuting the $X$ and $Y$ data within each bin, to...
David Chen, Rohan Hore, Rina Foygel Barber· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
