A central question in the era of big data is what to do with the enormous amount of
information. One possibility is to characterize it through statistics, eg, averages, or classify it …

We present a novel approach to simultaneously reconstruct the 3D structure of a non-rigid
coronary tree and estimate point correspondences between an input X-ray image and a …

The aim of using atypicality is to extract small, rare, unusual and interesting pieces out of big
data. This complements statistics about typical data to give insight into data. In order to find …

Anomaly detection refers to the problem of identifying abnormal behaviour within a set of
measurements. In many cases, one has some statistical model for normal data, and wishes …

This paper has dual aims. First is to develop practical universal coding methods for
unlabeled graphs. Second is to use these for graph anomaly detection. The paper develops …

A classic application of description length is for model selection with the minimum
description length (MDL) principle. The focus of this paper is to extend description length for …

With the exponential growth in information,“Big Data,” a key question is what to do with this
information. A classic possibility is to characterize it through statistics. The perspective in this …

Heart rate variability (HRV) is a vital measure of the autonomic nervous system functionality
and a key indicator of cardiovascular condition. This paper proposes a novel method, called …