In this paper we present a hybrid model for the demand acceptance variant of the routing and wavelength assignment problem in directed networks, an important benchmark problem in o...
A novel, two stage, neural architecture for the segmentation of range data and their modeling with undeformed superquadrics is presented. The system is composed by two distinct neu...
We present generative models dedicated to face recognition. Our models consider data extracted from color face images and use Bayesian Networks to model relationships between diffe...
—As the operating frequency of digital systems increases and voltage swing decreases, it becomes very important to characterize and analyze power distribution networks (PDNs) acc...
Wendemagegnehu T. Beyene, Chuck Yuan, Joong-Ho Kim...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...