30 citations · 36 across the 16 of their papers we have counts for
Showing 2021Show all
2 papers · 1 filter
cs.LG2021★ 30 cited
Enforcing fairness in private federated learning via the modified method of differential multipliers
Borja Rodríguez-Gálvez, Filip Granqvist, Rogier van Dalen +1
Federated learning with differential privacy, or private federated learning, provides a strategy to train machine learning models while respecting users' privacy. However, differen…
cs.LG2021★ 2 cited
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications
Matthias Paulik, Matt Seigel, Henry Mason +19
We describe the design of our federated task processing system. Originally, the system was created to support two specific federated tasks: evaluation and tuning of on-device ML sy…