1 citations · 1 across the 4 of their papers we have counts for
4 papers
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…
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…
FedControl: When Control Theory Meets Federated Learning
Adnan Ben Mansour, Gaia Carenini, Alexandre Duplessis +1
To date, the most popular federated learning algorithms use coordinate-wise averaging of the model parameters. We depart from this approach by differentiating client contributions…
Federated Learning Aggregation: New Robust Algorithms with Guarantees
Adnan Ben Mansour, Gaia Carenini, Alexandre Duplessis +1
Federated Learning has been recently proposed for distributed model training at the edge. The principle of this approach is to aggregate models learned on distributed clients to ob…