4 citations · 4 across the 3 of their papers we have counts for
3 papers
Separating common from salient patterns with Contrastive Representation Learning
Robin Louiset, Edouard Duchesnay, Antoine Grigis +1
Contrastive Analysis is a sub-field of Representation Learning that aims at separating common factors of variation between two datasets, a background (i.e., healthy subjects) and a…
Structured Sparse Principal Components Analysis with the TV-Elastic Net penalty
Amicie de Pierrefeu, Tommy Löfstedt, Fouad Hadj-Selem +4
Principal component analysis (PCA) is an exploratory tool widely used in data analysis to uncover dominant patterns of variability within a population. Despite its ability to repre…
Predictive support recovery with TV-Elastic Net penalty and logistic regression: an application to structural MRI
Mathieu Dubois, Fouad Hadj-Selem, Tommy Lofstedt +4
The use of machine-learning in neuroimaging offers new perspectives in early diagnosis and prognosis of brain diseases. Although such multivariate methods can capture complex relat…