This paper presents a general and efficient framework for probabilistic inference and learning from arbitrary uncertain information. It exploits the calculation properties of fini...
To design a transportation sensor network, the decision-maker needs to determine what sensor investments should be made, as well as when, how, where and with what technologies. Th...
Graphs are increasingly used to model a variety of loosely structured data such as biological or social networks and entityrelationships. Given this profusion of large-scale graph ...
Stephan Seufert, Srikanta J. Bedathur, Juliá...
This paper is devoted to the optimization problem of continuous multipartitioning, or multi-labeling, which is based on a convex relaxation of the continuous Potts model. In contr...
This paper proposes an adaptive multi-mode transmission strategy to improve the spectral efficiency achieved in the multiple-input multiple-output (MIMO) broadcast channel with d...
Jun Zhang, Marios Kountouris, Jeffrey G. Andrews, ...