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新算法应对带延迟的在线聚合问题

作者 PulseAugur 编辑部 · [1 个来源] ·

本文介绍了几种用于带延迟的直线度量在线聚合问题的新算法，重点关注学习增强和随机化方法。作者提出了一种名为Balance的确定性学习增强算法，提供了特定的鲁棒性和一致性保证。此外，还提出了一种随机算法，该算法针对无知对手可实现e+1的竞争比，优于现有的确定性基准，并为随机在线算法设定了新的下界。研究还将这些技术结合起来，开发了一种具有增强鲁棒性和一致性的随机学习增强算法。 AI

排序理由 该集群包含一篇详细介绍新算法和理论分析的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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新算法应对带延迟的在线聚合问题

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该集群包含一篇详细介绍新算法和理论分析的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.LG TIER_1 English(EN) · Tianhang Lu, Runtian Ren, Shengcai Liu, Ke Tang ·

    带延迟的线聚合的学习增强和随机算法

    arXiv:2607.27807v1 Announce Type: new Abstract: This paper studies learning-augmented and randomized online aggregation with delays on a line metric. We consider advice given as online suggested service lengths, and evaluate the algorithms in terms of robustness and consistency. …

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