most citedAdvancing Differential Privacy: Where We Are Now and Future Directions for Real-World Deployment

9 citations · 13 across the 4 of their papers we have counts for

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cs.LG2023★ 2 cited

Federated Linear Contextual Bandits with User-level Differential Privacy

Ruiquan Huang, Huanyu Zhang, Luca Melis +3

This paper studies federated linear contextual bandits under the notion of user-level differential privacy (DP). We first introduce a unified federated bandits framework that can a…

cs.LG2023★ 2 cited

DP-HyPO: An Adaptive Private Hyperparameter Optimization Framework

Hua Wang, Sheng Gao, Huanyu Zhang +2

Hyperparameter optimization, also known as hyperparameter tuning, is a widely recognized technique for improving model performance. Regrettably, when training private ML models, ma…