3 papers
cs.LG2026
Your Neighbors Know: Leveraging Local Neighborhoods for Backdoor Detection in Decentralized Learning
Sayan Biswas, Antoine Boutet, Davide Frey +7
Decentralized learning (DL) is an emerging machine learning paradigm where nodes collaboratively train models without a central server. However, the collaborative nature of DL make…
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.LG2025
Unified Privacy Guarantees for Decentralized Learning via Matrix Factorization
Aurélien Bellet, Edwige Cyffers, Davide Frey +3
Decentralized Learning (DL) enables users to collaboratively train models without sharing raw data by iteratively averaging local updates with neighbors in a network graph. This se…