2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Asynchronous Multi-Server Federated Learning for Geo-Distributed Clients
Yuncong Zuo, Bart Cox, Lydia Y. Chen +1
Federated learning (FL) systems enable multiple clients to train a machine learning model iteratively through synchronously exchanging the intermediate model weights with a single…
cs.LG2024★ 2 cited
Asynchronous Byzantine Federated Learning
Bart Cox, Abele Mălan, Lydia Y. Chen +1
Federated learning (FL) enables a set of geographically distributed clients to collectively train a model through a server. Classically, the training process is synchronous, but ca…
cs.LG2024★ 1 cited
Training Diffusion Models with Federated Learning
Matthijs de Goede, Bart Cox, Jérémie Decouchant
The training of diffusion-based models for image generation is predominantly controlled by a select few Big Tech companies, raising concerns about privacy, copyright, and data auth…