Markov logic networks (MLNs) combine first-order logic and Markov networks, allowing us to handle the complexity and uncertainty of real-world problems in a single consistent fram...
—Characterizing the performance of ad hoc networks is one of the most intricate open challenges; conventional ideas based on information-theoretic techniques and inequalities hav...
The Baldwin Effect is a very plausible, but unproven, biological theory concerning the power of learning to accelerate evolution. Simple computational models in the 1980’s gave...
Scheduling of transmissions is one of the most fundamental problems in the context of wireless networks. In this article, we consider the problem of computing power efficient sched...
ABSTRACT. Upon the discovery of power laws [8, 16, 30], a large body of work in complex network analysis has focused on developing generative models of graphs which mimick real-wor...