新研究探讨了带上限参与的Hessian相似优化

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 04:00

一篇题为“Hessian-Similar Optimization with Capped Participation: Lower Bounds and Virtual Masters”的新研究论文已在arXiv上发表。该论文介绍了在每轮只有部分客户端可以参与的情况下，新颖的优化技术。它为具有严格参与上限的算法设定了下界，并提出了一种使用Catalyst的虚拟主控方法，在二次问题上实现了改进的预期轮数。研究还包括一项比较所提出方法与现有算法的综合研究。 AI

影响引入了分布式优化新的理论界限和实用方法，可能提高大规模机器学习的效率。

排序理由该集群包含一篇发表在arXiv上的研究论文，详细介绍了新的优化技术。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv stat.ML 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv stat.ML TIER_1 English(EN) · Rui Wang · 2026-10-27 04:00

Hessian-相似优化与有界参与：下界与虚拟主控

arXiv:2610.33835v1 Announce Type: cross Abstract: What is the round complexity of Hessian-similar optimization when each round can contact at most $s$ of $m$ clients? Prior rates permit a free master or full participation and do not characterize strict caps. We count every one-ve…

本文如何被排名

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Hessian-相似优化与有界参与：下界与虚拟主控

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