Online social networks often involve very large numbers of users who share very large volumes of content. This content is increasingly being tagged with geo-spatial and temporal c...
Dario Freni, Carmen Ruiz Vicente, Sergio Mascetti,...
Several application contexts require the ability to use together and compare different geographic datasets (maps) concerning the same or overlapping areas. This is for example the...
Alberto Belussi, Barbara Catania, Paola Podest&agr...
Content–based image retrieval in the medical domain is an extremely hot topic in medical imaging as it promises to help better managing the large amount of medical images being ...
We present a probabilistic model-based framework for distributed learning that takes into account privacy restrictions and is applicable to scenarios where the different sites ha...
There has historically been very little concern with extrapolation in Machine Learning, yet extrapolation can be critical to diagnose. Predictor functions are almost always learne...