1 citations · 2 across the 8 of their papers we have counts for
4 papers · 1 filter
Interpretable machine learning for finding intermediate-mass black holes
Mario Pasquato, Piero Trevisan, Abbas Askar +4
Definitive evidence that globular clusters (GCs) host intermediate-mass black holes (IMBHs) is elusive. Machine learning (ML) models trained on GC simulations can in principle pred…
Tackling Computational Heterogeneity in FL: A Few Theoretical Insights
Adnan Ben Mansour, Gaia Carenini, Alexandre Duplessis
The future of machine learning lies in moving data collection along with training to the edge. Federated Learning, for short FL, has been recently proposed to achieve this goal. Th…
Sparse logistic regression for RR Lyrae vs binaries classification
Piero Trevisan, Mario Pasquato, Gaia Carenini +4
RR Lyrae (RRL) are old, low-mass radially pulsating variable stars in their core helium burning phase. They are popular stellar tracers and primary distance indicators, since they…
Adversarial Path Planning for Optimal Camera Positioning
Gaia Carenini, Alexandre Duplessis
The use of visual sensors is flourishing, driven among others by the several applications in detection and prevention of crimes or dangerous events. While the problem of optimal ca…