RR dominates SGD in smooth convex optimization under any reasonable stepsize after any finite number of epochs.
Tighter convergence bounds for shuffled sgd via primal-dual perspective
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Random Reshuffling Dominates Stochastic Gradient Descent
RR dominates SGD in smooth convex optimization under any reasonable stepsize after any finite number of epochs.