Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
We study the problem of minimum-distortion embedding of ultrametrics into the plane and higher dimensional spaces. Ultrametrics are a natural class of metrics that frequently occu...
Mihai Badoiu, Julia Chuzhoy, Piotr Indyk, Anastasi...
We study the topological simplification of graphs via random embeddings, leading ultimately to a reduction of the Gupta-Newman-Rabinovich-Sinclair (GNRS) L1 embedding conjecture t...
Fast retrieval using organ shapes is crucial in medical image databases since shape is a clinically prominent feature. In this paper, we propose that 2-D shapes in medical image da...
Graph drawing research traditionally focuses on producing geometric embeddings of graphs satisfying various aesthetic constraints. However additional work must still be done to dra...
Michael B. Dillencourt, David Eppstein, Michael T....