arXiv stat.ML
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A lower bound for stepsize-based acceleration of gradient descent
arXiv:2608.10418v1 Announce Type: cross Abstract: Recent work has shown that, for smooth convex optimization, plain gradient descent can be accelerated from its textbook convergence rate of $O(T^{-1})$ (where $T$ denotes the number of iterations) to $Obig(T^{-log_2(1+sqrt{2})}big)$ using carefully designed stepsize