We show that it is possible to use data compression on independently obtained hypotheses from various tasks to algorithmically provide guarantees that the tasks are sufficiently r...
Methods like DBSCAN are widely used in the analysis of spatial data. These methods are based on the neighborhood relations which use distance between points. However, these neighb...
Abstract. We propose an algorithm for the segmentation of blood vessels in the kind of CT-data typical for diagnostics in a clinical environment. Due to poor quality and variance i...
Background: Mean-based clustering algorithms such as bisecting k-means generally lack robustness. Although componentwise median is a more robust alternative, it can be a poor cent...
Yuanyuan Ding, Xin Dang, Hanxiang Peng, Dawn Wilki...
Using simulated data to develop and study diagnostic tools for data analysis is very beneficial. The user can gain insight about what happens when assumptions are violated since t...