We introduce three ensemble machine learning methods for analysis of biological DNA binding by transcription factors (TFs). The goal is to identify both TF target genes and their ...
A widely acknowledged drawback of many statistical modelling techniques, commonly used in machine learning, is that the resulting model is extremely difficult to interpret. A numb...
This paper presents the adaptation model used in NUCLEO, a pilot e-learning environment that is currently being developed at the Complutense University of Madrid. The NUCLEO syste...
In this paper we study the connection between sentiment of images expressed in metadata and their visual content in the social photo sharing environment Flickr. To this end, we co...
Stefan Siersdorfer, Enrico Minack, Fan Deng, Jonat...
In this paper, we propose a general framework for sparse semi-supervised learning, which concerns using a small portion of unlabeled data and a few labeled data to represent targe...