7 papers
Multi-rank Subspace Change-point Detection with Application in Monitoring Robotic Swarms
Jonghyeok Lee, Yao Xie, Youngser Park +3
We study real-time detection of low-rank changes in the covariance structure of high-dimensional streaming data, motivated by robotic swarm monitoring. Building on the spiked covar…
Change-Point Detection via Piecewise Linear Fitting Using MIP
Apoorva Narula, Santanu S. Dey, Yao Xie
We present a new mixed-integer programming (MIP) approach for offline multiple change-point detection by casting the problem as a globally optimal piecewise linear (PWL) fitting pr…
Point processes with event time uncertainty
Xiuyuan Cheng, Tingnan Gong, Yao Xie
Point processes are widely used statistical models for continuous-time discrete event data, such as medical records, crime reports, and social network interactions, to capture the…
Higher-criticism for sparse multi-stream change-point detection
Tingnan Gong, Alon Kipnis, Yao Xie
We study a statistical procedure based on higher criticism (HC) to address the sparse multi-stream quickest change-point detection problem. Namely, we aim to detect a potential cha…
Distribution-Free Online Change Detection for Low-Rank Images
Tingnan Gong, Seong-Hee Kim, Yao Xie
We present a distribution-free CUSUM procedure designed for online change detection in a time series of low-rank images, particularly when the change causes a mean shift. We repres…
Neural Spatiotemporal Point Processes: Trends and Challenges
Sumantrak Mukherjee, Mouad Elhamdi, George Mohler +4
Spatiotemporal point processes (STPPs) are probabilistic models for events occurring in continuous space and time. Real-world event data often exhibit intricate dependencies and he…