English(EN) Algorithmic Recourse Under Competition

新框架应对竞争场景下的算法追索权问题

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-01 04:00

研究人员开发了一个名为“竞争下的追索权”的新框架，以应对个人争夺有限资源时算法追索权的挑战。该框架旨在确保即使广泛实施可能改变接受阈值，追索权建议仍然有效。通过联合优化推荐接收者和必要的得分目标，该系统平衡了追索成本与最初被拒绝的个人的事后有效性。实验表明，个性化得分目标可以以更高的成本提高有效性，而共同得分目标在较低的有效性水平下提供了更好的成本-有效性权衡。 AI

影响这项研究可以提高机器学习系统中结果具有竞争性的公平性和准确性。

排序理由该集群包含一篇详细介绍算法追索权新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Shahin Jabbari · 2026-10-01 04:00

算法追索权与竞争

arXiv:2609.39877v1 Announce Type: cross Abstract: Algorithmic recourse provides individuals who have received undesirable outcomes from machine learning models with suggestions for minimum-cost improvements to achieve the desired outcome. A central assumption when computing recou…

本文如何被排名

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算法追索权与竞争

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