activity
20182022
most citedRobust Hypothesis Testing with Wasserstein Uncertainty Sets

6 citations · 7 across the 5 of their papers we have counts for

collaborators

7 papers

math.ST2022

Minimax Robust Quickest Change Detection using Wasserstein Ambiguity Sets

Liyan Xie

We study the robust quickest change detection under unknown pre- and post-change distributions. To deal with uncertainties in the data-generating distributions, we formulate two da…

stat.ME2022

PERCEPT: a new online change-point detection method using topological data analysis

Xiaojun Zheng, Simon Mak, Liyan Xie +1

Topological data analysis (TDA) provides a set of data analysis tools for extracting embedded topological structures from complex high-dimensional datasets. In recent years, TDA ha…

math.ST20216 cited

Robust Hypothesis Testing with Wasserstein Uncertainty Sets

Liyan Xie, Rui Gao, Yao Xie

We consider a data-driven robust hypothesis test where the optimal test will minimize the worst-case performance regarding distributions that are close to the empirical distributio…

math.ST20211 cited

Sequential (Quickest) Change Detection: Classical Results and New Directions

Liyan Xie, Shaofeng Zou, Yao Xie +1

Online detection of changes in stochastic systems, referred to as sequential change detection or quickest change detection, is an important research topic in statistics, signal pro…

math.ST2021

Optimality of Graph Scanning Statistic for Online Community Detection

Liyan Xie, Yao Xie

Sequential change-point detection for graphs is a fundamental problem for streaming network data types and has wide applications in social networks and power systems. Given fixed v…

math.ST2020

Sequential Change Detection by Optimal Weighted Divergence

Liyan Xie, Yao Xie

We present a new non-parametric statistic, called the weighed divergence, based on empirical distributions for sequential change detection. We start by constructing the we…