English(EN) Meta-LinEXP3: Online-within-Online Learning for Adversarial Linear Contextual Bandits

Meta-LinEXP3算法推进了对抗性线性上下文老虎机

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-16 04:00

研究人员推出了一种新颖的在线内在线学习算法Meta-LinEXP3，用于对抗性线性上下文老虎机。该算法旨在通过构建可预测的任务级先验来改进序列老虎机任务之间的知识转移。所提出的方法根据上下文分布是已知还是未知，提供不同的遗憾界限，并建立了先验准确性与转移遗憾减少之间的直接联系。实验表明Meta-LinEXP3的有效性，包括其在结构化高光谱张量采样中的应用。 AI

影响引入了一种用于对抗性线性上下文老虎机的新算法，可能改进序列学习任务中的知识转移。

排序理由该集群包含一篇详细介绍特定机器学习问题新算法的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

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报道来源 [1]

arXiv cs.LG TIER_1 English(EN) · Hao Li, Jie Xu, Zheng Xie · 2026-09-16 04:00

Meta-LinEXP3：对抗性线性上下文老虎机的在线内在线学习

arXiv:2609.09907v2 Announce Type: replace Abstract: Meta-learning has emerged as an effective paradigm for transferring knowledge across sequential bandit tasks. While substantial progress has been made for stochastic bandits and non-contextual adversarial bandits, meta-learning …

本文如何被排名

报道来源 [1]

Meta-LinEXP3：对抗性线性上下文老虎机的在线内在线学习

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