39 citations · 88 across the 7 of their papers we have counts for
3 papers · 1 filter
Siloed Federated Learning for Multi-Centric Histopathology Datasets
Mathieu Andreux, Jean Ogier du Terrail, Constance Beguier +1
While federated learning is a promising approach for training deep learning models over distributed sensitive datasets, it presents new challenges for machine learning, especially…
Efficient Sparse Secure Aggregation for Federated Learning
Constance Beguier, Mathieu Andreux, Eric W. Tramel
Federated Learning enables one to jointly train a machine learning model across distributed clients holding sensitive datasets. In real-world settings, this approach is hindered by…
Federated Survival Analysis with Discrete-Time Cox Models
Mathieu Andreux, Andre Manoel, Romuald Menuet +2
Building machine learning models from decentralized datasets located in different centers with federated learning (FL) is a promising approach to circumvent local data scarcity whi…