Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
We address distributed real-time applications represented by systems of non-preemptive dependent periodic tasks. This system is described by an acyclic directed graph. Because the...
Simulation composability is a difficult capability to achieve due to the challenges of creating components, selecting combinations of components, and integrating the selected comp...
Michael Roy Fox, David C. Brogan, Paul F. Reynolds...
We consider collusion in multi-unit auctions where the allocation and payments are determined using the VCG mechanism. We show how collusion can increase the utility of the collud...