21 citations · 24 across the 5 of their papers we have counts for
6 papers
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…
DeepLocalization: Using change point detection for Temporal Action Localization
Mohammed Shaiqur Rahman, Ibne Farabi Shihab, Lynna Chu +1
In this study, we introduce DeepLocalization, an innovative framework devised for the real-time localization of actions tailored explicitly for monitoring driver behavior. Utilizin…
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…
On the tightness of graph-based statistics
Lynna Chu, Hao Chen
We establish tightness of graph-based stochastic processes in the space with that allows for discontinuities of the first kind. The graph-based stochastic proces…
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…