In this paper we show that dimensionality reduction (i.e., Johnson-Lindenstrauss lemma) preserves not only the distances between static points, but also between moving points, and...
We describe a way of using multiple different types of similarity relationship to learn a low-dimensional embedding of a dataset. Our method chooses different, possibly overlappin...
Many natural image sets are samples of a low-dimensional manifold in the space of all possible images. When the image data set is not a linear combination of a small number of bas...
In this paper, we present a physics-based deformable model framework for the quantification of shape and motion parameters of the Left Anterior Descending (LAD) coronary artery in ...
We prove that local complementation and vertex deletion, operations from which vertexminors are defined, can simulate edge contractions. As an application, we prove that the rank...