3 papers
cs.LG2026
Mosaic Learning: A Framework for Decentralized Learning with Model Fragmentation
Sayan Biswas, Davide Frey, Romaric Gaudel +7
Decentralized learning (DL) enables collaborative machine learning (ML) without a central server, making it suitable for settings where training data cannot be centrally hosted. We…
cs.CR2025
Practical and Private Hybrid ML Inference with Fully Homomorphic Encryption
Sayan Biswas, Philippe Chartier, Akash Dhasade +7
In contemporary cloud-based services, protecting users' sensitive data and ensuring the confidentiality of the server's model are critical. Fully homomorphic encryption (FHE) enabl…
cs.LG2025
Robust ML Auditing using Prior Knowledge
Jade Garcia Bourrée, Augustin Godinot, Martijn De Vos +5
Among the many technical challenges to enforcing AI regulations, one crucial yet underexplored problem is the risk of audit manipulation. This manipulation occurs when a platform d…