2 citations · 2 across the 5 of their papers we have counts for
4 papers · 1 filter
High-Dimensional Change Point Detection via Graph Spanning Ratio
Katerina Papagiannouli, Yang-wen Sun, Vladimir Spokoiny
Inspired by graph-based methodologies, we introduce a novel graph-spanning algorithm designed to identify changes in both offline and online data across low to high dimensions. Thi…
Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss
Pierre Bréchet, Katerina Papagiannouli, Jing An +1
We consider a deep matrix factorization model of covariance matrices trained with the Bures-Wasserstein distance. While recent works have made advances in the study of the optimiza…
High dimensional change-point detection: a complete graph approach
Yang-Wen Sun, Katerina Papagiannouli, Vladimir Spokoiny
The aim of online change-point detection is for a accurate, timely discovery of structural breaks. As data dimension outgrows the number of data in observation, online detection be…
Online Graph-Based Change-Point Detection for High Dimensional Data
Yang-Wen Sun, Katerina Papagiannouli, Vladmir Spokoiny
Online change-point detection (OCPD) is important for application in various areas such as finance, biology, and the Internet of Things (IoT). However, OCPD faces major challenges…