In this paper we present two experiments conducted for comparison of different language identification algorithms. Short words-, frequent words- and n-gram-based approaches are co...
Lena Grothe, Ernesto William De Luca, Andreas N&uu...
We develop new techniques for time series classification based on hierarchical Bayesian generative models (called mixed-effect models) and the Fisher kernel derived from them. A k...
A computational model for the acquisition of knowledge from encyclopedic texts is described. The model has been implemented in a program, called SNOWY, that reads unedited texts f...
This paper deals with the analysis of temporal dependence in multivariate highfrequency time series data. The dependence structure between the marginal series is modelled through ...
In the general classification context the recourse to the so-called Bayes decision rule requires to estimate the class conditional probability density functions. In this paper we p...