40 citations · 83 across the 8 of their papers we have counts for
Showing 2019Show all
2 papers · 1 filter
cs.LG2019★ 40 cited
Privacy for Free: Communication-Efficient Learning with Differential Privacy Using Sketches
Tian Li, Zaoxing Liu, Vyas Sekar +1
Communication and privacy are two critical concerns in distributed learning. Many existing works treat these concerns separately. In this work, we argue that a natural connection e…
cs.LG2019★ 23 cited
Enhancing the Privacy of Federated Learning with Sketching
Zaoxing Liu, Tian Li, Virginia Smith +1
In response to growing concerns about user privacy, federated learning has emerged as a promising tool to train statistical models over networks of devices while keeping data local…