21 citations · 24 across the 5 of their papers we have counts for
4 papers · 1 filter
Adaptive Block-Based Change-Point Detection for Sparse Spatially Clustered Data with Applications in Remote Sensing Imaging
Alan Moore, Lynna Chu, Zhengyuan Zhu
We present a non-parametric change-point detection approach to detect potentially sparse changes in a time series of high-dimensional observations or non-Euclidean data objects. We…
A Robust Framework for Graph-based Two-Sample Tests Using Weights
Yichuan Bai, Lynna Chu
Graph-based tests are a class of non-parametric two-sample tests useful for analyzing high-dimensional data. The test statistics are constructed from similarity graphs (such as K-m…
Sequential Change-point Detection for High-dimensional and non-Euclidean Data
Lynna Chu, Hao Chen
In many applications, it is often of practical and scientific interest to detect anomaly events in a streaming sequence of high-dimensional or non-Euclidean observations. We study…
Asymptotic Distribution-Free Change-Point Detection for Multivariate and non-Euclidean Data
Lynna Chu, Hao Chen
We consider the testing and estimation of change-points, locations where the distribution abruptly changes, in a sequence of multivariate or non-Euclidean observations. We study a…