Learning probabilistic graphical models from high-dimensional datasets is a computationally challenging task. In many interesting applications, the domain dimensionality is such a...
One frequently studied problem in the context of information dissemination in communication networks is the broadcasting problem. In this paper, we study the following randomized b...
This paper describes a general purpose algorithm to segment any kind of lesions in CT images. The algorithm expects a click or a stroke inside the lesion from the user and learns ...
Bisimplicial edges in bipartite graphs are closely related to pivots in Gaussian elimination that avoid turning zeroes into non-zeroes. We present a new deterministic algorithm to...
Abstract: We propose a novel probabilistic method for detection of objects in noisy images. The method uses results from percolation and random graph theories. We present an algori...