2 papers
cs.LG2025
Distributionally Robust Federated Learning with Client Drift Minimization
Mounssif Krouka, Chaouki Ben Issaid, Mehdi Bennis
Federated learning (FL) faces critical challenges, particularly in heterogeneous environments where non-independent and identically distributed data across clients can lead to unfa…
cs.LG2019
Q-GADMM: Quantized Group ADMM for Communication Efficient Decentralized Machine Learning
Anis Elgabli, Jihong Park, Amrit S. Bedi +3
In this article, we propose a communication-efficient decentralized machine learning (ML) algorithm, coined quantized group ADMM (Q-GADMM). To reduce the number of communication li…