2 papers
cs.LG2025
Heterogeneous Federated Reinforcement Learning Using Wasserstein Barycenters
Luiz Pereira, M. Hadi Amini
In this paper, we first propose a novel algorithm for model fusion that leverages Wasserstein barycenters in training a global Deep Neural Network (DNN) in a distributed architectu…
cs.LG2025
Optimal Transport-based Domain Alignment as a Preprocessing Step for Federated Learning
Luiz Manella Pereira, M. Hadi Amini
Federated learning (FL) is a subfield of machine learning that avoids sharing local data with a central server, which can enhance privacy and scalability. The inability to consolid…