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The Relative Gaussian Mechanism and its Application to Private Gradient Descent.

, , and . AISTATS, volume 238 of Proceedings of Machine Learning Research, page 3079-3087. PMLR, (2024)

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Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives., , and . CoRR, (2018)A principled framework for the design and analysis of token algorithms.. CoRR, (2022)The Relative Gaussian Mechanism and its Application to Private Gradient Descent., , and . CoRR, (2023)Who Started This Rumor? Quantifying the Natural Differential Privacy of Gossip Protocols., , and . DISC, volume 179 of LIPIcs, page 8:1-8:18. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2020)Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees., , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 17343-17363. PMLR, (2023)An Optimal Algorithm for Decentralized Finite-Sum Optimization., , and . SIAM J. Optim., 31 (4): 2753-2783 (2021)Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives., , and . AISTATS, volume 89 of Proceedings of Machine Learning Research, page 897-906. PMLR, (2019)Accelerated Methods for Distributed Optimization. (Méthodes Accélérées pour l'Optimisation Distribuée).. Paris Sciences et Lettres University, France, (2021)Who started this rumor? Quantifying the natural differential privacy guarantees of gossip protocols., , and . CoRR, (2019)Fast Stochastic Bregman Gradient Methods: Sharp Analysis and Variance Reduction., , and . ICML, volume 139 of Proceedings of Machine Learning Research, page 2815-2825. PMLR, (2021)