… reach up to a scale of millions; cross-silo FL where clients are organizations or companies
and … of the cross-silo FL. More specifically, we first discuss applications of cross-silo FL and …

… in personalized cross-silo federated learning with non-IID … in personalized cross-silo federated
learning with non-IID data. … challenging personalized cross-silo federated learning prob…

… , a system solution for cross-silo FL that substantially reduces the … in FATE, an industrial
cross-silo FL framework. Evaluations … requirements posed by cross-silo federated learning. We …

… In this paper, we first propose a federated estimation method to accurately … training fair
models in cross-silo federated learning. We develop FedFair, a well-designed federated learning …

… Abstract—In cross-silo federated learning (FL), organizations cooperatively train a global
model with their local data. The organizations, however, may be heterogeneous in terms of …

… in federated learning. In particular, we show that meanregularized multi-task learning (MR-MTL),
a simple personalization framework, is a strong baseline for cross-silo FL: under …

… solution based on federated learning that uses decentralized … to develop a cross-silo machine
learning model that facilitates … to the cross-silo setting when discussing federated learning …

… lack of realistic cross-silo datasets, we propose FLamby, an open source cross-silo federated
… Our ambition is that FLamby becomes the reference benchmark for cross-silo FL, as LEAF […

… Federated learning usually employs a server-client … This approach may be inefficient in
cross-silo settings, as close-by … topology design for cross-silo federated learning using the theory …

… We focus on cross-silo FL, where clients are organizations with data that differ in their …
Clustered Federated Learning Similar to our algorithm, clustered federated learning partitions …