This work contributes to the robotic bin-picking problem, and more specifically to the problem of localizing piled box-like objects. We employ range imagery, and use box-like Supe...
In this paper novel theory to automate shape modelling is described. The main idea is to develop a theory that is intrinsically defined for curves, as opposed to a finite sample o...
—We describe parallel methods for solving large-scale, high-dimensional, sparse least-squares problems that arise in machine learning applications such as document classificatio...
MINLP problems are hard constrained optimization problems, with nonlinear constraints and mixed discrete continuous variables. They can be solved using a Branch-and-Bound scheme c...
We consider setting up sleep scheduling in sensor networks. We formulate the problem as an instance of the fractional domatic partition problem and obtain a distributed approximati...