Abstract. Two difficulties in designing data-centric routes [2–5] in wireless sensor networks are the lack of reasonably practical data aggregation models and the high computatio...
Network programming is notoriously hard to understand: one has to deal with a variety of protocols (IP, ICMP, UDP, TCP etc), concurrency, packet loss, host failure, timeouts, the c...
Learning graphical models with hidden variables can offer semantic insights to complex data and lead to salient structured predictors without relying on expensive, sometime unatta...
Abstract—In this paper we ask which properties of a distributed network can be computed from a few amount of local information provided by its nodes. The distributed model we con...
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...