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English(EN) Silver Rate Is (Almost) Optimal for Gradient Descent Acceleration

新研究推进机器学习随机优化 · 跟踪5个来源

作者 PulseAugur 编辑部 · [5 个来源] ·

几篇近期研究论文探讨了随机优化技术的进展，特别关注梯度下降及其变体在复杂机器学习问题中的应用。其中一篇论文表明，即使存在重尾噪声，标准的随机梯度下降上升（SGDA）也能收敛，而无需梯度裁剪，并为正则化问题引入了新的无裁剪算法。另一项研究通过关注梯度映射，在约束凸凹极小极大优化方面取得了近乎最优的收敛率。此外，研究还探讨了平滑凸目标函数的随机梯度下降（SGD）的精确收敛率，确立了理论极限，并分析了使用预定步长的梯度下降加速的最优性。最后，一篇论文详细描述了常数步长随机逼近的特性，提供了有限时间收敛保证和高阶定量高斯近似。 AI

影响 这些优化算法的理论进展可能导致更高效、更鲁棒的机器学习模型训练。

排序理由 多篇arXiv论文详细介绍了机器学习优化算法的理论进展。

在 arXiv cs.LG 阅读 →

AI 生成摘要 · Google Gemini · 来自 5 个来源。 我们如何撰写摘要 →

新研究推进机器学习随机优化 · 跟踪5个来源

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多篇arXiv论文详细介绍了机器学习优化算法的理论进展。
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报道来源 [5]

  1. arXiv cs.AI TIER_1 English(EN) · Tianxi Zhu, Yi Xu, Xiangyang Ji ·

    梯度修正对重尾非凸随机极小极大优化的作用

    arXiv:2609.06064v1 Announce Type: cross Abstract: Stochastic min-max optimization has attracted increasing attention due to its applications in modern machine learning, while existing theoretical studies mainly rely on the bounded variance assumption for stochastic gradients. Und…

  2. arXiv cs.LG TIER_1 English(EN) · Ahmet Alacaoglu ·

    如何为受约束的随机极小极大问题及其他问题缩小梯度映射

    arXiv:2609.08380v1 Announce Type: cross Abstract: We study the stochastic first-order oracle complexity for constrained or regularized convex-concave min-max optimization and stochastic monotone variational inequalities. We focus on the case when suboptimality is measured in term…

  3. arXiv cs.LG TIER_1 English(EN) · Ruijie Li, Kang Chen, Tianyu Wang ·

    光滑凸目标上随机梯度下降的精确时齐率前沿

    arXiv:2609.08537v1 Announce Type: cross Abstract: We study the time-uniform convergence of the raw iterate of standard stochastic gradient descent (SGD) for unconstrained smooth convex objectives. We prove that, under standard noise assumptions, the time-uniform convergence rate …

  4. arXiv cs.LG TIER_1 English(EN) · Yuhan Ye, Kaizhao Liu ·

    银价（几乎）是梯度下降加速的最优值

    arXiv:2609.09152v1 Announce Type: cross Abstract: We study how far gradient descent (GD) can be accelerated by predetermined nonnegative 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{\…

  5. arXiv cs.LG TIER_1 English(EN) · Zedong Wang, Yuyang Wang, Ijay Narang, Felix Wang, Yuzhou Wang, Siva Theja Maguluri ·

    恒定步长随机逼近：有限时间收敛、高斯逼近和尾部界限

    arXiv:2602.13960v2 Announce Type: replace Abstract: Constant-stepsize stochastic approximation (SA) is widely used in learning for computational efficiency, yet the distribution of the iterates is typically intractable. Classical asymptotics results give $X_k^{(\alpha)} \approx X…

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