This paper uses network packet capture data to demonstrate how Robust Principal
Component Analysis (RPCA) can be used in a new way to detect anomalies which serve as …

A theory and algorithm for detecting and classifying weak, distributed patterns in network
data is presented. The patterns we consider are anomalous temporal correlations between …

We present a theory and algorithm for detecting and classifying weak, distributed patterns in
network data that provide actionable information with quantiable measures of uncertainty …

Herein we describe theory and algorithms for detecting covariance structures in large, noisy
data sets. Our work uses ideas from matrix completion and robust principal component …

Typically, network structures are represented by one of three different representation
matrices: the adjacency matrix, the unnormalised and the normalised graph Laplacian …

The US government imposes reporting requirements on healthcare providers as health
metrics are important for assessing and improving the US healthcare system. However …

Designing computer networks resilient to failures, excessive loads, and attacks and then
monitoring them are challenged by a range of issues inherent to networks. These limitations …