Deep belief networks are a powerful way to model complex probability distributions. However, it is difficult to learn the structure of a belief network, particularly one with hidd...
Ryan Prescott Adams, Hanna M. Wallach, Zoubin Ghah...
We provide a general framework for the analysis of the capacity scaling properties in mobile ad-hoc networks with heterogeneous nodes and spatial inhomogeneities. Existing analyti...
—We envision new communication paradigms, using physical dynamic interconnectedness among people. Delay Tolerant Networks (DTNs) are a new communication paradigm to support such ...
In this paper, we propose a genetic network programming (GNP) architecture using a coevolution model called automatically defined groups (ADG). The GNP evolves networks for describ...
The characteristics of ad hoc networks naturally encourage the deployment of distributed services. Although current networks implement group communication methods, they do not sup...