Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
work, applies a nonlinear transformation from the input space to the hidden space. The output layer Partial face images, e.g.1 eyes, nose, and ear supplies the response of the netw...
In this paper, we consider a class of sensor networks where the data is not required in real-time by an observer; for example, a sensor network monitoring a scientific phenomenon ...
Sameer Tilak, Nael B. Abu-Ghazaleh, Wendi Rabiner ...
Recent years have witnessed the emergence of shared sensor networks as integrated infrastructure for multiple applications. It is important to allocate multiple applications in a ...
You Xu, Abusayeed Saifullah, Yixin Chen, Chenyang ...
—It is important in communication networks to use routes that are as short as possible (i.e have low stretch) while keeping routing tables small. Recent advances in compact routi...