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Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning.

, , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 5924-5963. PMLR, (2023)

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Private and Efficient Meta-Learning with Low Rank and Sparse Decomposition., , , , , , , and . CoRR, (2022)Differentially Private Image Classification from Features., , , , and . Trans. Mach. Learn. Res., (2023)Why Is Public Pretraining Necessary for Private Model Training?, , , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 10611-10627. PMLR, (2023)Towards Large Scale Transfer Learning for Differentially Private Image Classification., , , and . Trans. Mach. Learn. Res., (2023)Improved Differentially Private and Lazy Online Convex Optimization., , , and . CoRR, (2023)Improved Differential Privacy for SGD via Optimal Private Linear Operators on Adaptive Streams., , , , and . NeurIPS, (2022)Differentially Private Model Personalization., , , , and . NeurIPS, page 29723-29735. (2021)Private Stochastic Convex Optimization with Optimal Rates., , , and . NeurIPS, page 11279-11288. (2019)Privacy-preserving Data Mining in Industry., , and . WSDM, page 840-841. ACM, (2019)(Near) Dimension Independent Risk Bounds for Differentially Private Learning., and . ICML, volume 32 of JMLR Workshop and Conference Proceedings, page 476-484. JMLR.org, (2014)