标题： 共形变化点定位 显示英文标题

标题： Conformal changepoint localization

摘要： 变点定位问题是估计有序数据列表的数据生成分布中发生改变的索引的问题，或者声明没有发生改变。 我们提出了广泛适用的CONCH（CONformal CHangepoint localization）算法，该算法使用一个由校准p值组成的矩阵，在前变和后变分布各自可交换的温和假设下，生成单个变点的置信区间。 我们在各种合成数据集和真实数据集上展示了CONCH算法的应用，包括使用黑盒预训练分类器来检测图像或文本序列中的变化。 显示英文摘要

摘要： Changepoint localization is the problem of estimating the index at which a change occurred in the data generating distribution of an ordered list of data, or declaring that no change occurred. We present the broadly applicable CONCH (CONformal CHangepoint localization) algorithm, which uses a matrix of conformal p-values to produce a confidence interval for a (single) changepoint under the mild assumption that the pre-change and post-change distributions are each exchangeable. We exemplify the CONCH algorithm on a variety of synthetic and real-world datasets, including using black-box pre-trained classifiers to detect changes in sequences of images or text.