English(EN) Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies

新算法解决副本有限的在线公平划分问题

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-02 04:00

研究人员开发了新的在线公平划分算法，解决了大量不可分割物品和少数副本的场景。这些算法将问题建模为上下文老虎机问题，旨在通过学习基于物品-代理特征的效用函数来平衡公平性和效率。所提出的方法实现了可证明的次线性遗憾，并在实验结果中显示出有效性。 AI

影响为资源分配问题引入了新颖的算法方法，这些方法可以应用于管理用户-物品分配的AI系统中。

排序理由这是一篇详细介绍机器学习特定问题新算法的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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

本文如何被排名

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arXiv stat.ML TIER_1 English(EN) · Arun Verma, Indrajit Saha, Makoto Yokoo, Bryan Kian Hsiang Low · 2026-09-02 04:00

皆大欢喜：在线分配稀缺多物品公平分割问题

arXiv:2408.12845v3 Announce Type: replace-cross Abstract: This paper considers a novel variant of the online fair division problem involving multiple agents in which a learner sequentially observes an indivisible item that must be irrevocably allocated to one of the agents to ach…