1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.CL2022★ 1 cited
Training Mixed-Domain Translation Models via Federated Learning
Peyman Passban, Tanya Roosta, Rahul Gupta +2
Training mixed-domain translation models is a complex task that demands tailored architectures and costly data preparation techniques. In this work, we leverage federated learning…
cs.LG2022★ 1 cited
Learnings from Federated Learning in the Real world
Christophe Dupuy, Tanya G. Roosta, Leo Long +3
Federated Learning (FL) applied to real world data may suffer from several idiosyncrasies. One such idiosyncrasy is the data distribution across devices. Data across devices could…