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arXiv Machine Learning By Sanghoon Yu, Min-hwan Oh

Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates

Read the original on arXiv Machine Learning →

arXiv:2606. 00984v1 Announce Type: cross Abstract: We study linear contextual bandits under rare parameter updates: the learner may incorporate reward feedback into its parameter estimate only at a small number of update times, while still observing contexts online and selecting actions sequentially.

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