Paper recorded by Signals 4 on 2026-11-03 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-11-03 on arXiv · recorded by Signals 4 on 2026-11-04
Category: cs.LG · 机器学习 · first seen 2026-11-04
Conformal prediction gives finite-sample coverage when calibration and test points are exchangeable, but exchangeability can fail when deployment changes the data distribution. We study conformal prediction in performative settings, where the deployed predictor affects the data distribution, and seek prediction sets valid at performative equilibrium: coverage must hold under $D(f^\star)$ for a per