Boolean networks have long been used as models of molecular networks and play an increasingly important role in systems biology. This paper describes a software package, offered ...
In this paper, we propose a post randomization technique to learn a Bayesian network (BN) from distributed heterogeneous data, in a privacy sensitive fashion. In this case, two or ...
We consider distributed estimation of a deterministic vector parameter from noisy sensor observations in a wireless sensor network (WSN). The observation noise is assumed uncorrela...
Abstract--In the current environment of rapidly changing invehicle requirements and ever-increasing functional content for automotive EE systems, there are several sources of uncer...
Arkadeb Ghosal, Haibo Zeng, Marco Di Natale, Yakov...
— We consider a network of distributed sensors, where each sensor takes a linear measurement of some unknown parameters, corrupted by independent Gaussian noises. We propose a si...