Traditional stereo algorithms estimate disparity at the same resolution as the observations. In this work we address the problem of estimating disparity and occlusion information ...
We observe that the classical maximum flow problem in any directed planar graph G can be reformulated as a parametric shortest path problem in the oriented dual graph G . This ref...
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
The Synchronous Dataflow (SDF) model of computation is popular for modelling the timing behaviour of real-time embedded hardware and software systems and applications. It is an es...
In this paper, we propose to use graph-mining techniques to understand the communication pattern within a data-centre. We model the communication observed within a data-centre as a...
Maitreya Natu, Vaishali P. Sadaphal, Sangameshwar ...