Feature extraction is a process that extracts salient features from observed variables. It is considered a promising alternative to overcome the problems of weight and structure o...
In recent years there has been a flurry of works on learning Bayesian networks from data. One of the hard problems in this area is how to effectively learn the structure of a beli...
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
We consider the following network design problem. We are given an undirected network with costs on the edges, a set of terminals, and an upper bound for each terminal limiting the ...
Samuel Fiorini, Gianpaolo Oriolo, Laura Sanit&agra...
— In this paper, we analyze the impact of straight line routing in large homogeneous multi-hop wireless networks. We estimate the nodal load, which is defined as the number of p...