标题： 用于多个变点检测的融合Lasso群组 显示英文标题

标题： The group fused Lasso for multiple change-point detection

摘要： 我们提出了组融合Lasso方法以检测一组共现的一维信号所共享的多个变化点。通过在多维总变差上施加约束来逼近原始信号，从而检测出变化点，这导致分段常数逼近。提出了快速算法来精确地或近似地解决由此产生的优化问题。当信号数量增加时，给出了两个算法一致性的条件，并通过模拟数据和数组比较基因组杂交数据提供了实证证据以支持结果。 显示英文摘要

摘要： We present the group fused Lasso for detection of multiple change-points shared by a set of co-occurring one-dimensional signals. Change-points are detected by approximating the original signals with a constraint on the multidimensional total variation, leading to piecewise-constant approximations. Fast algorithms are proposed to solve the resulting optimization problems, either exactly or approximately. Conditions are given for consistency of both algorithms as the number of signals increases, and empirical evidence is provided to support the results on simulated and array comparative genomic hybridization data.