EcoSta 2022: Start Registration
View Submission - EcoSta2022
A0531
Title: Factorized binary search: Change point detection in the network structure of multivariate high-dimensional time series Authors:  Ivor Cribben - Alberta School of Business (Canada) [presenting]
Abstract: The purpose is to introduce factorized binary search (FaBiSearch), a novel change point detection method in the network structure of multivariate high-dimensional time series. FaBiSearch uses non-negative matrix factorization, an unsupervised dimension reduction technique, and a new binary search algorithm to identify multiple change points. In addition, we propose a new method for network estimation for data between change points. We show that FaBiSearch outperforms another state-of-the-art method on simulated data sets and we apply FaBiSearch to a resting-state and to a task-based fMRI data set.