English(EN) ShapleyOG: Fast Adaptive Shapley Value Estimation with Odd Gaussian Processes

ShapleyOG方法加速了机器学习中Shapley值的估计

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-06 05:00

研究人员开发了ShapleyOG，一种用于估计机器学习中Shapley值的新颖方法，该方法显著降低了计算开销。通过关注博弈的奇数分量，ShapleyOG所需的观测次数比以前的自适应方法少，同时保持了估计的准确性。这一进步使得自适应Shapley值估计对于评估成本更高、预算更大的博弈变得可行，并且优于最先进的非自适应估计器。 AI

影响通过使Shapley值估计在计算上更可行，加速了可解释性技术在机器学习中的应用。

排序理由这是一篇详细介绍机器学习中估计Shapley值新方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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报道来源 [1]

arXiv stat.ML TIER_1 English(EN) · David Rundel, R. Teal Witter, Santo M. A. R. Thies, Matthias Feurer, Fabian Fumagalli, Bernd Bischl · 2026-11-06 05:00

ShapleyOG：使用奇高斯过程进行快速自适应Shapley值估计

arXiv:2611.07173v1 Announce Type: new Abstract: Shapley values are a central tool for attribution in machine learning. Since their exact computation requires evaluating the cooperative game to be explained on exponentially many player coalitions, they are typically estimated from…

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ShapleyOG：使用奇高斯过程进行快速自适应Shapley值估计

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