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News/Adaptive Exploration for Latent-State Bandits
arxiv
PublishedJune 2, 2026 at 4:00 AM
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Adaptive Exploration for Latent-State Bandits

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Publisher summary· verbatim

arXiv:2602.05139v3 Announce Type: replace Abstract: We study bandits whose rewards depend on an unobserved Markov state that evolves independently of the learner's actions. The optimal arm can change even though the learner observes only past actions and rewards. We propose algorithms that feed LinU

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Mentioned models
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  • 01
    LinUCB
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arxiv
Read original ↗All from arxiv →
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#bandits#machine-learning#markov-state

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Mentioned models
01
  • 01
    LinUCB
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
03
#bandits#machine-learning#markov-state

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