— Uniform sampling in networks is at the core of a wide variety of randomized algorithms. Random sampling can be performed by modeling the system as an undirected graph with asso...
Asad Awan, Ronaldo A. Ferreira, Suresh Jagannathan...
This paper presents a distributed Bayesian fault diagnosis scheme for physical systems. Our diagnoser design is based on a procedure for factoring the global system bond graph (BG...
Indranil Roychoudhury, Gautam Biswas, Xenofon D. K...
We describe and evaluate a system for learning domainspecific control knowledge. In particular, given a planning domain, the goal is to output a control policy that performs well ...
In life science, deeper understanding of biomolecular systems is acquired by computational modeling and analysis. For the modeling of several kinds of reaction networks, e.g. sign...
Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...