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Apr, 2021
在线性情境下利用良好表示的策略性宝藏
Leveraging Good Representations in Linear Contextual Bandits
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Matteo Papini, Andrea Tirinzoni, Marcello Restelli, Alessandro Lazaric, Matteo Pirotta
TL;DR
本文针对线性语境劫掠问题,提出新的选择算法来适应多种线性表示方法,通过实验证明了我们算法的可行性和优越性。
Abstract
The
linear contextual bandit
literature is mostly focused on the design of efficient learning algorithms for a given
representation
. However, a contextual bandit problem may admit multiple linear representations,
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