Recently proposed l1-regularized maximum-likelihood optimization methods for learning sparse Markov networks result into convex problems that can be solved optimally and efficien...
This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
This paper reviews the model of interactive Markov chains (IMCs, for short), an extension of labelled transition systems with exponentially delayed transitions. We show that IMCs a...
One of the most critical issues in femtocell network deployment is interference management, especially for femtocells sharing the spectrum occupied by conventional cellular networ...
Abstract--Domain knowledge for web applications is currently being made available as domain ontology with the advent of the semantic web, in which semantics govern relationships am...