55 citations · 285 across the 20 of their papers we have counts for
3 papers · 1 filter
Compression Boosts Differentially Private Federated Learning
Raouf Kerkouche, Gergely Ács, Claude Castelluccia +1
Federated Learning allows distributed entities to train a common model collaboratively without sharing their own data. Although it prevents data collection and aggregation by excha…
Federated Learning in Adversarial Settings
Raouf Kerkouche, Gergely Ács, Claude Castelluccia
Federated Learning enables entities to collaboratively learn a shared prediction model while keeping their training data locally. It prevents data collection and aggregation and, t…
DESIRE: A Third Way for a European Exposure Notification System Leveraging the best of centralized and decentralized systems
Claude Castelluccia, Nataliia Bielova, Antoine Boutet +4
This document presents an evolution of the ROBERT protocol that decentralizes most of its operations on the mobile devices. DESIRE is based on the same architecture than ROBERT but…