To discover patterns in historical data, climate scientists have applied various clustering methods with the goal of identifying regions that share some common climatological beha...
Karsten Steinhaeuser, Nitesh V. Chawla, Auroop R. ...
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
In this work we propose a novel approach to anomaly detection in streaming communication data. We first build a stochastic model for the system based on temporal communication pa...
Real-time surveillance systems, network and telecommunication systems, and other dynamic processes often generate tremendous (potentially infinite) volume of stream data. Effectiv...
Y. Dora Cai, David Clutter, Greg Pape, Jiawei Han,...
A fast exploratory framework for extracting cardiac noise signals contained in rest-case fMRI images is presented. Highly autocorrelated, independent components of the input time ...