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English(EN) Generalized Regret Analysis of Thompson Sampling using Fractional Posteriors

新的汤普森采样变体“alpha-TS”提供通用遗憾分析

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了汤普森采样（一种流行的解决随机多臂老虎机问题的算法）的通用遗憾分析。这种新方法，称为“alpha-TS”，通过一个因子“alpha”来调整似然度，从而使用分数后验分布而不是标准后验分布。该分析在先验和奖励分布的温和条件下，产生了实例依赖和实例独立的频率遗憾界限，适用于亚高斯和指数族模型。推导出的界限与现有的改进型UCB界限相匹配，并且不需要闭式或共轭先验等特定结构属性。 AI

影响 这一遗憾分析的理论进展可能导致更高效的多臂老虎机算法，影响在线学习和推荐系统等领域。

排序理由 该集群包含一篇详细介绍现有算法新理论分析的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv stat.ML 阅读 →

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新的汤普森采样变体“alpha-TS”提供通用遗憾分析

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该集群包含一篇详细介绍现有算法新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 stat.ML TIER_1 English(EN) · Prateek Jaiswal, Debdeep Pati, Anirban Bhattacharya, Bani K. Mallick ·

    基于分数后验的汤普森采样通用遗憾分析

    arXiv:2309.06349v2 Announce Type: replace Abstract: Thompson sampling (TS) is one of the most popular and earliest algorithms to solve stochastic multi-armed bandit problems. We consider a variant of TS, named $\alpha$-TS, where we use a fractional or $\alpha$-posterior ($\alpha\…

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