Author of the publication

Why Does Differential Privacy with Large Epsilon Defend Against Practical Membership Inference Attacks?

, , , , , and . CoRR, (2024)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

 

Other publications of authors with the same name

Locally Differentially Private Federated Learning: Efficient Algorithms with Tight Risk Bounds., and . CoRR, (2021)FERMI: Fair Empirical Risk Minimization via Exponential Rényi Mutual Information., , , , and . CoRR, (2021)A Stochastic Optimization Framework for Fair Risk Minimization., , , , and . Trans. Mach. Learn. Res., (2022)Optimal Differentially Private Learning with Public Data., , , and . CoRR, (2023)Private Federated Learning Without a Trusted Server: Optimal Algorithms for Convex Losses., and . ICLR, OpenReview.net, (2023)Efficient Search of First-Order Nash Equilibria in Nonconvex-Concave Smooth Min-Max Problems., , and . SIAM J. Optim., 31 (4): 2508-2538 (2021)Output Perturbation for Differentially Private Convex Optimization with Improved Population Loss Bounds, Runtimes and Applications to Private Adversarial Training., and . CoRR, (2021)Why Does Differential Privacy with Large Epsilon Defend Against Practical Membership Inference Attacks?, , , , , and . CoRR, (2024)Private Non-Convex Federated Learning Without a Trusted Server., , and . AISTATS, volume 206 of Proceedings of Machine Learning Research, page 5749-5786. PMLR, (2023)How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization., , and . CoRR, (2024)