标题： 统一不同的确认预测理论 显示英文标题

标题： Unifying Different Theories of Conformal Prediction

摘要： 本文提出了一种统一框架，用以理解非参数预测（conformal prediction）文献中多种方法背后的原理与理论，其中包括标准非参数预测（CP）、加权非参数预测（WCP）、非可交换非参数预测（NexCP）以及随机局部化非参数预测（RLCP）等。 我们框架的核心思想在于，非参数方法基于揭示现有数据的部分信息，并假设在给定部分信息条件下数据的条件分布。 不同的方法源于部分信息的不同选择，以及相应的（近似）条件分布的选择。 除了重新获得并统一现有的结果外，我们的框架还为现有方法提供了新的理论保证，并扩展了非参数预测方法论。 显示英文摘要

摘要： This paper presents a unified framework for understanding the methodology and theory behind several different methods in the conformal prediction literature, which includes standard conformal prediction (CP), weighted conformal prediction (WCP), nonexchangeable conformal prediction (NexCP), and randomly-localized conformal prediction (RLCP), among others. At the crux of our framework is the idea that conformal methods are based on revealing partial information about the data at hand, and positing a conditional distribution for the data given the partial information. Different methods arise from different choices of partial information, and of the corresponding (approximate) conditional distribution. In addition to recovering and unifying existing results, our framework leads to both new theoretical guarantees for existing methods, and new extensions of the conformal methodology.