 Little is Enough: Improving Privacy by Sharing Labels in Federated
Semi-Supervised LearningAAAI Conference on Artificial Intelligence (AAAI), 2023 |
 Truthful Generalized Linear ModelsWorkshop on Internet and Network Economics (WINE), 2022 |
 Private Graph Data Release: A SurveyACM Computing Surveys (CSUR), 2021 |
 A Graph Symmetrisation Bound on Channel Information Leakage under
Blowfish PrivacyIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2020 |
 Federated Learning and Differential Privacy: Software tools analysis,
the Sherpa.ai FL framework and methodological guidelines for preserving data
privacy |
 Distributionally-Robust Machine Learning Using Locally
Differentially-Private DataOptimization Letters (Optim. Lett.), 2020 |
 Differential Privacy at Risk: Bridging Randomness and Privacy BudgetProceedings on Privacy Enhancing Technologies (PoPETs), 2020 |
 SoK: Differential PrivaciesProceedings on Privacy Enhancing Technologies (PoPETs), 2019 |
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