We study the problem of image denoising where images are assumed to be samples from low dimensional (sub)manifolds. We propose the algorithm of locally linear denoising. The algor...
Estimating divergence between two point processes, i.e. probability laws on the space of spike trains, is an essential tool in many computational neuroscience applications, such a...
The theory of intersection homology was developed to study the singularities of a topologically stratified space. This paper incorporates this theory into the already developed f...
Computer scientists have made ceaseless efforts to replicate cognitive video understanding abilities
of human brains onto autonomous vision systems. As video surveillance cameras ...
As cluster computers are used for a wider range of applications, we encounter the need to deliver resources at particular times, to meet particular deadlines, and/or at the same t...