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Large language models can be strong differentially private learners
X Li, F Tramer, P Liang, T Hashimoto - ar** in private sgd: A geometric perspective
Deep learning models are increasingly popular in many machine learning applications
where the training data may contain sensitive information. To provide formal and rigorous …
where the training data may contain sensitive information. To provide formal and rigorous …
Fast-adapting and privacy-preserving federated recommender system
In the mobile Internet era, recommender systems have become an irreplaceable tool to help
users discover useful items, thus alleviating the information overload problem. Recent …
users discover useful items, thus alleviating the information overload problem. Recent …
Deep learning with gaussian differential privacy
Deep learning models are often trained on datasets that contain sensitive information such
as individuals' shop** transactions, personal contacts, and medical records. An …
as individuals' shop** transactions, personal contacts, and medical records. An …
On privacy and personalization in cross-silo federated learning
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 cross …
federated learning (FL), there is a lack of work considering DP and its implications for cross …
Automatic clip**: Differentially private deep learning made easier and stronger
Per-example gradient clip** is a key algorithmic step that enables practical differential
private (DP) training for deep learning models. The choice of clip** threshold $ R …
private (DP) training for deep learning models. The choice of clip** threshold $ R …