English(EN) Variance-Optimal Off-Policy Evaluation with Conjunct Effect Modeling

新的VOCEM估计器降低了离轨策略评估中的方差

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-07 04:00

研究人员开发了一种名为方差最优结合效应模型（VOCEM）的新估计器，用于上下文老虎机策略的离轨策略评估。该方法旨在通过在现有估计器OffCEM和双重稳健（DR）之间进行插值来降低与动作级重要性加权相关的高方差。VOCEM选择一个插值系数来最小化方差，从而得到一个方差不大于OffCEM或DR的估计器。在合成数据和基准测试上的实验表明，VOCEM在各种条件下均优于OffCEM和DR，显示出改进的稳定性和经验鲁棒性。 AI

影响提高了上下文老虎机策略评估的稳定性和鲁棒性，可能带来更可靠的强化学习系统。

排序理由该集群包含一篇详细介绍离轨策略评估新估计器的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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Newsworthiness bucket: Tool; 该集群包含一篇详细介绍离轨策略评估新估计器的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.LG TIER_1 English(EN) · Nicol\`o Felicioni, Michael Benigni, Maurizio Ferrari Dacrema, Paolo Cremonesi · 2026-10-07 04:00

具有联合效应建模的方差最优策略外评估

arXiv:2610.08677v1 Announce Type: new Abstract: Off-policy evaluation (OPE) for contextual bandit policies becomes challenging when action-level importance weighting incurs excessive variance. Doubly robust (DR) estimation remains unbiased under common support but retains these h…

本文如何被排名

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具有联合效应建模的方差最优策略外评估

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