3 citations · 5 across the 4 of their papers we have counts for
4 papers
Covariance scanning for adaptively optimal change point detection in high-dimensional linear models
Haeran Cho, Housen Li
This paper investigates the detection and estimation of a single change in high-dimensional linear models. We derive minimax lower bounds for the detection boundary and the estimat…
Estimation and Inference for Change Points in Functional Regression Time Series
Shivam Kumar, Haotian Xu, Haeran Cho +1
In this paper, we study the estimation and inference of change points under a functional linear regression model with changes in the slope function. We present a novel Functional R…
Detection and inference of changes in high-dimensional linear regression with non-sparse structures
Haeran Cho, Tobias Kley, Housen Li
For data segmentation in high-dimensional linear regression settings, the regression parameters are often assumed to be sparse segment-wise, which enables many existing methods to…
High-dimensional data segmentation in regression settings permitting temporal dependence and non-Gaussianity
Haeran Cho, Dom Owens
We propose a data segmentation methodology for the high-dimensional linear regression problem where regression parameters are allowed to undergo multiple changes. The proposed meth…