ing the differential semantics of rule-based models: exact and automated model reduction (Invited Lecture) Vincent Danos∗§, J´erˆome Feret†, Walter Fontana‡, Russell Harme...
Self-adjusting computation is an evaluation model in which programs can respond efficiently to small changes to their input data by using a change-propagation mechanism that updat...
Meta-modeling is well known to define the basic concepts of domain-specific languages in an object-oriented way. Based on graph transformation, an abstract meta-model may be enhanc...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
In this paper we compare and contrast two approaches to Machine Translation (MT): the CMU-UKA Syntax Augmented Machine Translation system (SAMT) and UPC-TALP N-gram-based Statisti...