Abstract. We propose a privacy-preserving formulation of a linear program whose constraint matrix is partitioned into groups of columns where each group of columns and its correspo...
Abstract. Traditional seizure detection algorithms act on single channels ignoring the synchronously recorded, inherently interdependent multichannel nature of EEG. However, the sp...
Borbala Hunyadi, Maarten De Vos, Marco Signoretto,...
Abstract. We present a Bayesian translational model for matching patterns in data sets which have neither co-occurring samples nor variables, but only a similar experiment design d...
Tommi Suvitaival, Ilkka Huopaniemi, Matej Oresic, ...
Attribute importance measures for supervised learning are important for improving both learning accuracy and interpretability. However, it is well-known there could be bias when th...
Abstract. In many supervised learning tasks it can be costly or infeasible to obtain objective, reliable labels. We may, however, be able to obtain a large number of subjective, po...