In this paper we introduce a new task model that is specifically targeted towards representing stream processing applications. Examples of such applications are those involved in...
Automotive companies are forced to continuously extend and improve their product line-up. However, increasing diversity, higher design complexity, and shorter development cycles c...
Axel Blumenstock, Christoph Schlieder, Markus M&uu...
Methods for learning Bayesian networks can discover dependency structure between observed variables. Although these methods are useful in many applications, they run into computat...
Eran Segal, Dana Pe'er, Aviv Regev, Daphne Koller,...
In the standard formalization of supervised learning problems, a datum is represented as a vector of features without prior knowledge about relationships among features. However, ...
Background: Phylogenetic networks are a generalization of phylogenetic trees that allow for the representation of evolutionary events acting at the population level, like recombin...