gn problem can be abstractly characterized as a constrained function-to-structure mapping. The de sign task takes as input the specifications of the desired functions of a device...
We propose a variance-component probabilistic model for sparse signal reconstruction and model selection. The measurements follow an underdetermined linear model, where the unknown...
One of the known problems with shared object manipulation in virtual environments is the disruptive effect of network lag in collaboration sessions. Most solutions to this problem...
When intelligent systems reason about complex problems with a large hierarchical classification space it is hard to evaluate system performance. For classification problems, differ...
An ensemble is a group of learning models that jointly solve a problem. However, the ensembles generated by existing techniques are sometimes unnecessarily large, which can lead t...