The importance of bringing causality into play when designing feature selection methods is more and more acknowledged in the machine learning community. This paper proposes a filt...
Machine learning often relies on costly labeled data, and this impedes its application to new classification and information extraction problems. This has motivated the developme...
Separating machine printed text and handwriting from overlapping text is a challenging problem in the document analysis field and no reliable algorithms have been developed thus f...
Most studies in statistical or machine learning based authorship attribution focus on two or a few authors. This leads to an overestimation of the importance of the features extra...
In this paper we investigate the problem of locating singing voice in music tracks. As opposed to most existing methods for this task, we rely on the extraction of the characteris...