61 citations · 113 across the 15 of their papers we have counts for
3 papers · 1 filter
On Privacy and Personalization in Cross-Silo Federated Learning
Ziyu Liu, Shengyuan Hu, Zhiwei Steven Wu +1
While the application of differential privacy (DP) has been well-studied in cross-device federated learning (FL), there is a lack of work considering DP and its implications for cr…
FedSynth: Gradient Compression via Synthetic Data in Federated Learning
Shengyuan Hu, Jack Goetz, Kshitiz Malik +3
Model compression is important in federated learning (FL) with large models to reduce communication cost. Prior works have been focusing on sparsification based compression that co…
Fair Federated Learning via Bounded Group Loss
Shengyuan Hu, Zhiwei Steven Wu, Virginia Smith
Fair prediction across protected groups is an important constraint for many federated learning applications. However, prior work studying group fair federated learning lacks formal…