English(EN) Non-Adaptive 1-Bit Mean Estimation: Minimax Rates and the Sample-Interval Tradeoff

新研究表明非自适应协议在 1 位均值估计中可匹配自适应速率

作者 PulseAugur 编辑部 · [2 个来源] · 2026-09-08 10:52

一篇新研究论文探讨了在 1 位通信约束下分布式均值估计的非自适应协议。该研究表明，非自适应方法可以达到与自适应方法相同的最优速率，挑战了先前关于多阶段交互必要性的假设。该研究还量化了这些估计器中样本复杂性与区间约束之间的权衡。 AI

影响这项研究有助于在通信约束下对分布式机器学习的理论理解，可能影响未来的算法设计。

排序理由该集群包含一篇在 arXiv 上发表的研究论文，详细介绍了机器学习方面的新理论发现。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

本文如何被排名

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arXiv cs.LG TIER_1 English(EN) · Ivan Lau, Jonathan Scarlett · 2026-09-10 04:00

非自适应1比特均值估计：Minimax率与样本-区间权衡

arXiv:2609.08564v1 Announce Type: cross Abstract: We study distributed one-dimensional mean estimation under a 1-bit communication constraint. Each agent observes one sample, drawn independently from an unknown distribution, and returns a single bit in response to a query $Q: \ma…
Hugging Face Daily Papers TIER_1 English(EN) · 2026-09-08 10:52

非自适应1比特均值估计：Minimax率与样本-区间权衡

We study distributed one-dimensional mean estimation under a 1-bit communication constraint. Each agent observes one sample, drawn independently from an unknown distribution, and returns a single bit in response to a query $Q: \mathbb{R}\to\{0,1\}$ chosen by a central learner. Th…