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Silver Rate Is (Almost) Optimal for Gradient Descent

arxiv.org/abs/2609.09152

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Updated 1 h ago · first seen 11 Sept 2026

paper_01M294FTRD90WTVYH8YM21201W

Published
11 Sept 2026
T1 · 1 h ago
arXiv
2609.09152
T1 · 1 h ago
Category
math.OC
T1 · 1 h ago

Abstract

-cross Abstract: We study how far gradient descent (GD) can be accelerated by predetermined stepsizes in smooth convex optimization. Writing $p_{\mathrm{sil}}=\log_2(1+\sqrt{2})$, we prove an $\Omega\left(n^{-p_{\mathrm{sil}}-O(\sqrt{\log\log n/\log n})}\right)$ non-anytime lower bound. In the anytime setting, every infinite schedule has infinitely many horizons with error $\Omega\left(n^{-\frac{2p_{\mathrm{sil}}}{1+p_{\mathrm{sil}}}-O(\sqrt{\log\log n/\log n})}\right)$. Together with the silver-schedule upper bound [Altschuler and Parrilo, 2025] and the anytime upper bound [Zhang et al., 2025], our results determine the optimal polynomial convergence exponents in both settings.

Authors 2

Yuhan Ye, Kaizhao Liu

Specification

Official page

Source:arXiv (Atom API + RSS)T1observed 1 h agohigh

Arxiv announce type
replace

Source:arXiv (Atom API + RSS)T1observed 1 h agohigh

arXiv id
2609.09152

Source:arXiv (Atom API + RSS)T1observed 1 h agohigh

Categories
math.OC, cs.LG

Source:arXiv (Atom API + RSS)T1observed 1 h agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 1 h agohigh

Primary category
math.OC

Source:arXiv (Atom API + RSS)T1observed 1 h agohigh

Published
11 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 1 h agohigh

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Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

1 h ago

Conflicts

None