1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CR2026
Multi-tier Differential Private Query Release
Shaowei Wang, Jinn Li, Yun Peng +5
Answering statistical queries over sensitive data under differential privacy (DP) is a common task in many settings, including databases, mobile computing, and data markets. In the…
cs.CR2023★ 1 cited
BAGEL: Backdoor Attacks against Federated Contrastive Learning
Yao Huang, Kongyang Chen, Jiannong Cao +5
Federated Contrastive Learning (FCL) is an emerging privacy-preserving paradigm in distributed learning for unlabeled data. In FCL, distributed parties collaboratively learn a glob…
cs.CR2023
Privacy Amplification via Shuffling: Unified, Simplified, and Tightened
Shaowei Wang, Yun Peng, Jin Li +5
The shuffle model of differential privacy provides promising privacy-utility balances in decentralized, privacy-preserving data analysis. However, the current analyses of privacy a…