21 citations · 62 across the 11 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
Evaluating Privacy Leakage in Split Learning
Xinchi Qiu, Ilias Leontiadis, Luca Melis +2
Privacy-Preserving machine learning (PPML) can help us train and deploy models that utilize private information. In particular, on-device machine learning allows us to avoid sharin…