We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...
Most probabilistic inference algorithms are specified and processed on a propositional level. In the last decade, many proposals for algorithms accepting first-order specificat...
Task reallocation in a multi-robot organization is a process that distributes a decomposed global task to individual robots. This process must be distributed and dynamic because i...
Many large scale systems, like grids and structured peer to peer systems, operate on a constrained topology. Since underlying networks do not expose the real topology to the appli...
It has been recently shown that calibration with an error less than ∆ > 0 is almost surely guaranteed with a randomized forecasting algorithm, where forecasts are obtained by...