This paper studies distributed networked systems with data dropouts and transmission delays. We propose a decentralized eventtriggering scheme, where a subsystem broadcasts its sta...
Dependency networks are a compelling alternative to Bayesian networks for learning joint probability distributions from data and using them to compute probabilities. A dependency ...
—Characterizing user churn has become an important topic in studying P2P networks, both in theoretical analysis and system design. Recent work [26] has shown that direct sampling...
Background: Transcriptional gene regulation is one of the most important mechanisms in controlling many essential cellular processes, including cell development, cell-cycle contro...
Marc Bailly-Bechet, Alfredo Braunstein, Andrea Pag...
Abstract. Gaussian graphical models are widely used to tackle the important and challenging problem of inferring genetic regulatory networks from expression data. These models have...