2 citations · 2 across the 1 of their papers we have counts for
2 papers
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…
stat.ML2018
Protection Against Reconstruction and Its Applications in Private Federated Learning
Abhishek Bhowmick, John Duchi, Julien Freudiger +2
In large-scale statistical learning, data collection and model fitting are moving increasingly toward peripheral devices---phones, watches, fitness trackers---away from centralized…