3 papers
stat.ML2022
Multi-task longitudinal forecasting with missing values on Alzheimer's Disease
Carlos Sevilla-Salcedo, Vandad Imani, Pablo M. Olmos +2
Machine learning techniques typically applied to dementia forecasting lack in their capabilities to jointly learn several tasks, handle time dependent heterogeneous data and missin…
stat.ML2020
Bayesian Sparse Factor Analysis with Kernelized Observations
Carlos Sevilla-Salcedo, Alejandro Guerrero-López, Pablo M. Olmos +1
Multi-view problems can be faced with latent variable models since they are able to find low-dimensional projections that fairly capture the correlations among the multiple views t…
stat.ML2020
Sparse Semi-supervised Heterogeneous Interbattery Bayesian Analysis
Carlos Sevilla-Salcedo, Vanessa Gómez-Verdejo, Pablo M. Olmos
The Bayesian approach to feature extraction, known as factor analysis (FA), has been widely studied in machine learning to obtain a latent representation of the data. An adequate s…