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Towards Federated Learning at Scale: System Design, , , , , , , , , and 4 other author(s). (2019)cite arxiv:1902.01046.Generative Models for Effective ML on Private, Decentralized Datasets., , , , , , , and . CoRR, (2019)Ad click prediction: a view from the trenches, , , , , , , , , and 1 other author(s). Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, page 1222--1230. ACM, (2013)Communication-Efficient Learning of Deep Networks from Decentralized Data, , , , and . (2016)Distributed Mean Estimation with Limited Communication., , , and . CoRR, (2016)Federated Learning of Deep Networks using Model Averaging., , , and . CoRR, (2016)Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and Implicit Updates. CoRR, (2010)A survey of Algorithms and Analysis for Adaptive Online Learning.. J. Mach. Learn. Res., (2017)Follow-the-Regularized-Leader and Mirror Descent: Equivalence Theorems and L1 Regularization.. AISTATS, volume 15 of JMLR Proceedings, page 525-533. JMLR.org, (2011)Multi-Epoch Matrix Factorization Mechanisms for Private Machine Learning., , , and . CoRR, (2022)