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News/Large-Step Last-Iterate Convergence of Random-Reshuffling Stochastic Gradient Descent
arxiv
PublishedOctober 15, 2026 at 4:00 AM

Large-Step Last-Iterate Convergence of Random-Reshuffling Stochastic Gradient Descent

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Publisher summary· verbatim

arXiv:2610.19444v1 Announce Type: cross Abstract: Random reshuffling stochastic gradient descent (RR-SGD) is widely used for finite-sum optimization in machine learning. For convex $L$-smooth components, recent work establishes convergence guarantees for an averaged iterate with component stepsizes

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