3 citations · 3 across the 2 of their papers we have counts for
3 papers · 1 filter
Toward provably private learning from federated data
Katharine Daly, Yu Xiao, Zachary Garrett +9
Federated Learning (FL) allows devices with private data to collaborate in training a shared model. We present a next-generation FL system based on Trusted Execution Environments (…
Toward provably private analytics and insights into GenAI use
Albert Cheu, Artem Lagzdin, Brett McLarnon +8
Large-scale systems that compute analytics over a fleet of devices must achieve high privacy and security standards while also meeting data quality, usability, and resource efficie…
Confidential Federated Computations
Hubert Eichner, Daniel Ramage, Kallista Bonawitz +11
Federated Learning and Analytics (FLA) have seen widespread adoption by technology platforms for processing sensitive on-device data. However, basic FLA systems have privacy limita…