This paper reviews recent developments in fundamental limits and optimal algorithms for
change point analysis. We focus on minimax optimal rates in change point detection and …

In this paper, we first introduce the multilayer random dot product graph (MRDPG) model,
which can be seen as an extension of the random dot product graph model to multilayer …

We study the problem of online network change point detection. In this setting, a collection of
independent Bernoulli networks is collected sequentially, and the underlying distributions …

We investigate sequential change point estimation and detection in univariate
nonparametric settings, where a stream of independent observations from sub-Gaussian …

Given a sequence of random (directed and weighted) graphs, we address the problem of
online monitoring and detection of changes in the underlying data distribution. Our idea is to …

Graphs are fundamental mathematical structures used in various fields to model statistical
and physical relationships between data, signals, and processes. In some applications, such …

We study the following online network change point detection settings: A time series of
independent, possibly sparse Bernoulli networks whose distributions might change at an …

We consider a high-dimensional dynamic pricing problem under non-stationarity, where a
firm sells products to $ T $ sequentially arriving consumers that behave according to an …

We present an online community change detection algorithm called spectral CUSUM to
detect the emergence of a community using a subspace projection procedure based on a …

We consider the problem of sequential graph topology change-point detection from graph
signals. We assume that signals on the nodes of the graph are regularized by the underlying …