BriefGPT.xyz
Jun, 2021
分布偏移下的自适应符合推断
Adaptive Conformal Inference Under Distribution Shift
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Isaac Gibbs, Emmanuel Candès
TL;DR
本文提出了一种自适应的线上学习方法 - 自适应符合推断方法，该方法结合了预测集和符合推断的思想，能够在任何黑箱模型中实现长时间内预期的覆盖概率，从而解决了数据变化扰动的问题。
Abstract
We develop methods for forming
prediction sets
in an online setting where the data generating distribution is allowed to vary over time in an unknown fashion. Our framework builds on ideas from
conformal inference
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