We study an approximation for the zero-variance change of measure to estimate the probability of a rare event in a continuous-time Markov chain. The rare event occurs when the cha...
Pieter-Tjerk de Boer, Pierre L'Ecuyer, Gerardo Rub...
— This paper analyzes two classes of consensus algorithms in presence of bounded measurement errors. The protocols taken into account adopt an updating rule based either on const...
We derive lower bounds on the convergence speed of a widely used class of distributed averaging algorithms. In particular, we prove that any distributed averaging algorithm whose ...
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Abstract--The dynamics of a rule-based gene regulatory network are determined by the regulatory functions in conjunction with whatever probability distributions are involved in net...