: Modern society relies heavily on complex software systems for everyday activities. Dependability of these systems thus has become a critical feature that determines which product...
Monte Carlo techniques have long been used (since Buffon's experiment to approximate the value of by tossing a needle onto striped paper) to analyze phenomena which, due to ...
Samarn Chantaravarapan, Ali K. Gunal, Edward J. Wi...
Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
Background: Predicting protein complexes from experimental data remains a challenge due to limited resolution and stochastic errors of high-throughput methods. Current algorithms ...
Wasinee Rungsarityotin, Roland Krause, Arno Sch&ou...
One of the fundamental problems in distributed computing is how to efficiently perform routing in a faulty network in which each link fails with some probability. This paper inves...