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...
—Both the communication limitation and the measurement properties based algorithm become the bottleneck of enhancing the traditional power system state estimation speed. The avai...
—The rapid scaling up of Networked Control Systems (NCS) is forcing traditional single-hop shared medium industrial fieldbuses (a.k.a. fieldbuses) to evolve toward multi-hop sw...
—Wireless sensor networks (WSNs) are networks of distributed autonomous devices that can sense or monitor physical or environmental conditions cooperatively. WSNs face many chall...
Raghavendra V. Kulkarni, A. Forster, Ganesh K. Ven...
Recently, the generative modeling approach to video segmentation has been gaining popularity in the computer vision community. For example, the flexible sprites framework has been...