Ordering information is a difficult but a important task for natural language generation applications. A wrong order of information not only makes it difficult to understand, but a...
Bayesian networks are graphical representations of probability distributions. In virtually all of the work on learning these networks, the assumption is that we are presented with...
Background: With the explosion of microarray studies, an enormous amount of data is being produced. Systematic integration of gene expression data from different sources increases...
Abstract. Branch predictors are associated with critical design issues for nowadays instruction greedy processors. We study two important domains where the optimization of decision...
Patrick Carribault, Christophe Lemuet, Jean-Thomas...
We study the dynamics of information propagation in environments of low-overhead personal publishing, using a large collection of weblogs over time as our example domain. We chara...
Daniel Gruhl, Ramanathan V. Guha, David Liben-Nowe...