3 papers
cs.LG2025
Heterogeneity Matters even More in Distributed Learning: Study from Generalization Perspective
Masoud Kavian, Romain Chor, Milad Sefidgaran +1
In this paper, we investigate the effect of data heterogeneity across clients on the performance of distributed learning systems, i.e., one-round Federated Learning, as measured by…
stat.ML2023
Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often!
Milad Sefidgaran, Romain Chor, Abdellatif Zaidi +1
We investigate the generalization error of statistical learning models in a Federated Learning (FL) setting. Specifically, we study the evolution of the generalization error with t…
stat.ML2023
More Communication Does Not Result in Smaller Generalization Error in Federated Learning
Romain Chor, Milad Sefidgaran, Abdellatif Zaidi
We study the generalization error of statistical learning models in a Federated Learning (FL) setting. Specifically, there are devices or clients, each holding an independent o…